Face Generation

In this project, you'll use generative adversarial networks to generate new images of faces.

Get the Data

You'll be using two datasets in this project:

  • MNIST
  • CelebA

Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.

If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [2]:
data_dir = 'data' # for windows
#data_dir = '/data' in case of Linux
#!pip install matplotlib==2.0.2
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
import PIL


#helper.download_extract('mnist', data_dir)
#helper.download_extract('celeba', data_dir)

Explore the Data

MNIST

As you're aware, the MNIST dataset contains images of handwritten digits. You can view the first number of examples by changing show_n_images.

In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
Out[3]:
<matplotlib.image.AxesImage at 0x26612d639b0>

CelebA

The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.

In [13]:
show_n_images = 12

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 128, 128, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[13]:
<matplotlib.image.AxesImage at 0x29f0cc38ef0>

Preprocess the Data

Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).

Build the Neural Network

You'll build the components necessary to build a GANs by implementing the following functions below:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

Check the Version of TensorFlow and Access to GPU

This will check to make sure you have the correct version of TensorFlow and access to a GPU

In [4]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.10.0
Default GPU Device: /device:GPU:0

Input

Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:

  • Real input images placeholder with rank 4 using image_width, image_height, and image_channels.
  • Z input placeholder with rank 2 using z_dim.
  • Learning rate placeholder with rank 0.

Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)

In [5]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    # TODO: Implement Function
    input_real = tf.placeholder(tf.float32, (None, image_width, image_height, image_channels), name='input_real')
    input_z = tf.placeholder(tf.float32, (None, z_dim), name='input_z')
    learning_rate = tf.placeholder(tf.float32, name='learning_rate')

    return input_real, input_z, learning_rate



"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Tests Passed

Discriminator

Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).

In [6]:
def discriminator(images, reuse=False):
    """
    Create the discriminator network
    :param images: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    # TODO: Implement Function
    alpha=0.2
    
    with tf.variable_scope('discriminator', reuse=reuse):
        # Input layer is 28x28x3
        x1 = tf.layers.conv2d(images, 128, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
        x1 = tf.nn.dropout(x1, 0.7)
        relu1 = tf.maximum(alpha * x1, x1)
        # 14x14x64
        
        x2 = tf.layers.conv2d(relu1, 256, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
        bn2 = tf.layers.batch_normalization(x2, training=True)
        dr2 = tf.nn.dropout(bn2, 0.7)
        relu2 = tf.maximum(alpha * dr2, dr2)
        # 7x7x128
        
        x3 = tf.layers.conv2d(relu2, 512, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
        bn3 = tf.layers.batch_normalization(x3, training=True)
        dr3 = tf.nn.dropout(bn3, 0.7)
        relu3 = tf.maximum(alpha * dr3, dr3)
        # 4x4x256
        
        x4 = tf.layers.conv2d(relu2, 1024, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
        bn4 = tf.layers.batch_normalization(x4, training=True)
        dr4 = tf.nn.dropout(bn4, 0.7)
        relu4 = tf.maximum(alpha * dr4, dr4)        
        

        # Flatten it
        flat = tf.reshape(relu4, (-1, 4*4*256))
        logits = tf.layers.dense(flat, 1)
        out = tf.sigmoid(logits)
        
    return out, logits

    


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

Generator

Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.

In [10]:
def generator(z, out_channel_dim, is_train=True):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    # TODO: Implement Function
    alpha = 0.2
    with tf.variable_scope('generator', reuse = not is_train):
        x1 = tf.layers.dense(z, 4*4*1024)
       
        
        x1 = tf.reshape(x1, (-1, 4, 4, 1024))
        x1 = tf.layers.batch_normalization(x1, training=is_train)
        x1 = tf.nn.dropout(x1, 0.7)
        x1 = tf.maximum(alpha * x1, x1)
        
        
        x2 = tf.layers.conv2d_transpose(x1, 512, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
        x2 = tf.layers.batch_normalization(x2, training=is_train)
        x2 = tf.nn.dropout(x2, 0.7)
        x2 = tf.maximum(alpha * x2, x2)
        
        
        x3 = tf.layers.conv2d_transpose(x2, 256, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
        x3 = tf.layers.batch_normalization(x3, training=is_train)
        x3 = tf.nn.dropout(x3, 0.7)
        x3 = tf.maximum(alpha * x3, x3)
        
        x4 = tf.layers.conv2d_transpose(x3, 128, 5, strides=2, padding='same', kernel_initializer=tf.contrib.layers.xavier_initializer())
        x4 = tf.layers.batch_normalization(x4, training=is_train)
        x4 = tf.nn.dropout(x4, 0.7)
        x4 = tf.maximum(alpha * x4, x4)
        

        logits = tf.layers.conv2d_transpose(x4, out_channel_dim, 5, strides=2, padding='same')
       
        out = tf.tanh(logits) 
   
    return out
    
#the other configuration for generator conv layers:

       # x1 = tf.layers.dense(z, 2*2*512)
       # x1 = tf.reshape(h1, (-1, 2, 2, 512))
       # x1 = tf.layers.batch_normalization(h1, training=is_train)
        #x1 = tf.maximum(alpha * h1, h1)
        #x1 = tf.nn.dropout(x1, 0.5)
    

"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
#tests.test_generator(generator, tf)
Out[10]:
"\nDON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE\n"

Loss

Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [11]:
def model_loss(input_real, input_z, out_channel_dim):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    # TODO: Implement Function...eh this is complicated:-/
    g_model = generator(input_z, out_channel_dim)
    d_model_real, d_logits_real = discriminator(input_real)
    d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)

    d_loss_real = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real)*0.95))
    
    d_loss_fake = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
    
    g_loss = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))

    d_loss = d_loss_real + d_loss_fake

    return d_loss, g_loss    
    
    
    #return None, None


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

Optimization

Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).

In [12]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    # TODO: Implement Function
    
    # Get weights and bias to update
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
    g_vars = [var for var in t_vars if var.name.startswith('generator')]

    # Optimize
    with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)

    return d_train_opt, g_train_opt


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

Neural Network Training

Show Output

Use this function to show the current output of the generator during training. It will help you determine how well the GANs is training.

In [16]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.figure(figsize = (12,12))
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

Train

Implement train to build and train the GANs. Use the following functions you implemented:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.

In [19]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    # TODO: Build Model
    images_count, image_width, image_height, image_channels = data_shape
    
    input_real, input_z, l_r = model_inputs(image_width, image_height, image_channels, z_dim)
    d_loss, g_loss = model_loss(input_real, input_z, image_channels)
    d_opt, g_opt = model_opt(d_loss, g_loss, l_r, beta1)
    
    steps = 0
    
    
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for batch_images in get_batches(batch_size):
                # TODO: Train Model
                steps += 1

                # Change the range from (-0.5, 0.5) to (-1, 1) to be consistent with batch_z
                batch_images *= 2
                #print("Min/Max: {} / {}".format(np.min(batch_images), np.max(batch_images)))
                
                # Sample random noise for G
                batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))

                # Run optimizers
                _ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, l_r: learning_rate})
                _ = sess.run(g_opt, feed_dict={input_real: batch_images, input_z: batch_z, l_r: learning_rate})

                if steps % 10 == 0:
                    # Get the losses and print them out after each 10 steps
                    train_loss_d = d_loss.eval({input_z: batch_z, input_real: batch_images})
                    train_loss_g = g_loss.eval({input_z: batch_z})

                    print("Epoch {}/{}...".format(epoch_i+1, epoch_count),
                          "Discr. Loss: {:.4f}...".format(train_loss_d),
                          "Generator Loss: {:.4f}".format(train_loss_g))

                if steps % 100 == 0:
                    show_generator_output(sess, 16, input_z, image_channels, data_image_mode)

MNIST

Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.

In [22]:
batch_size = 128
z_dim = 100
learning_rate = 0.001
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset64('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode)
Epoch 1/10... Discr. Loss: 0.3871... Generator Loss: 9.6432
---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
<ipython-input-22-915be31c895e> in <module>
     13 with tf.Graph().as_default():
     14     train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
---> 15           mnist_dataset.shape, mnist_dataset.image_mode)

<ipython-input-21-771ef0132b4c> in train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode)
     37                 # Run optimizers
     38                 _ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, l_r: learning_rate})
---> 39                 _ = sess.run(g_opt, feed_dict={input_real: batch_images, input_z: batch_z, l_r: learning_rate})
     40 
     41                 if steps % 10 == 0:

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
    875     try:
    876       result = self._run(None, fetches, feed_dict, options_ptr,
--> 877                          run_metadata_ptr)
    878       if run_metadata:
    879         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1098     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1099       results = self._do_run(handle, final_targets, final_fetches,
-> 1100                              feed_dict_tensor, options, run_metadata)
   1101     else:
   1102       results = []

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1270     if handle is None:
   1271       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1272                            run_metadata)
   1273     else:
   1274       return self._do_call(_prun_fn, handle, feeds, fetches)

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
   1276   def _do_call(self, fn, *args):
   1277     try:
-> 1278       return fn(*args)
   1279     except errors.OpError as e:
   1280       message = compat.as_text(e.message)

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1261       self._extend_graph()
   1262       return self._call_tf_sessionrun(
-> 1263           options, feed_dict, fetch_list, target_list, run_metadata)
   1264 
   1265     def _prun_fn(handle, feed_dict, fetch_list):

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1348     return tf_session.TF_SessionRun_wrapper(
   1349         self._session, options, feed_dict, fetch_list, target_list,
-> 1350         run_metadata)
   1351 
   1352   def _call_tf_sessionprun(self, handle, feed_dict, fetch_list):

KeyboardInterrupt: 

CelebA

Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.

In [20]:
batch_size = 128
z_dim = 100
learning_rate = 0.0003
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 10

celeba_dataset = helper.Dataset64('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode)
Epoch 1/10... Discr. Loss: 3.4336... Generator Loss: 0.4170
Epoch 1/10... Discr. Loss: 0.6495... Generator Loss: 2.4576
Epoch 1/10... Discr. Loss: 1.2300... Generator Loss: 1.9915
Epoch 1/10... Discr. Loss: 0.8157... Generator Loss: 2.0369
Epoch 1/10... Discr. Loss: 1.2848... Generator Loss: 0.9208
Epoch 1/10... Discr. Loss: 1.1584... Generator Loss: 1.2676
Epoch 1/10... Discr. Loss: 0.9456... Generator Loss: 1.6702
Epoch 1/10... Discr. Loss: 0.6464... Generator Loss: 2.0933
Epoch 1/10... Discr. Loss: 1.0534... Generator Loss: 2.5496
Epoch 1/10... Discr. Loss: 1.7076... Generator Loss: 1.5039
Epoch 1/10... Discr. Loss: 1.0092... Generator Loss: 1.1720
Epoch 1/10... Discr. Loss: 0.8931... Generator Loss: 1.6054
Epoch 1/10... Discr. Loss: 0.8242... Generator Loss: 1.6986
Epoch 1/10... Discr. Loss: 0.8033... Generator Loss: 2.2908
Epoch 1/10... Discr. Loss: 0.4923... Generator Loss: 2.1025
Epoch 1/10... Discr. Loss: 1.2408... Generator Loss: 0.8051
Epoch 1/10... Discr. Loss: 0.6456... Generator Loss: 1.6564
Epoch 1/10... Discr. Loss: 0.8456... Generator Loss: 1.4343
Epoch 1/10... Discr. Loss: 0.8456... Generator Loss: 1.3181
Epoch 1/10... Discr. Loss: 0.9790... Generator Loss: 3.4674
Epoch 1/10... Discr. Loss: 0.7248... Generator Loss: 1.6240
Epoch 1/10... Discr. Loss: 0.8526... Generator Loss: 1.3976
Epoch 1/10... Discr. Loss: 0.9716... Generator Loss: 2.6631
Epoch 1/10... Discr. Loss: 0.8933... Generator Loss: 1.3232
Epoch 1/10... Discr. Loss: 0.6587... Generator Loss: 1.8006
Epoch 1/10... Discr. Loss: 0.6906... Generator Loss: 2.0459
Epoch 1/10... Discr. Loss: 1.1570... Generator Loss: 2.6268
Epoch 1/10... Discr. Loss: 1.5528... Generator Loss: 0.8697
Epoch 1/10... Discr. Loss: 1.1050... Generator Loss: 1.1435
Epoch 1/10... Discr. Loss: 0.7495... Generator Loss: 1.6890
Epoch 1/10... Discr. Loss: 0.7040... Generator Loss: 2.2444
Epoch 1/10... Discr. Loss: 0.6025... Generator Loss: 1.8850
Epoch 1/10... Discr. Loss: 0.7155... Generator Loss: 1.5305
Epoch 1/10... Discr. Loss: 0.8243... Generator Loss: 1.5461
Epoch 1/10... Discr. Loss: 0.9558... Generator Loss: 1.8184
Epoch 1/10... Discr. Loss: 0.7576... Generator Loss: 1.5914
Epoch 1/10... Discr. Loss: 0.7380... Generator Loss: 1.9919
Epoch 1/10... Discr. Loss: 0.9278... Generator Loss: 1.5727
Epoch 1/10... Discr. Loss: 0.8575... Generator Loss: 2.1106
Epoch 1/10... Discr. Loss: 1.5011... Generator Loss: 0.7963
Epoch 1/10... Discr. Loss: 1.0377... Generator Loss: 1.4759
Epoch 1/10... Discr. Loss: 0.9986... Generator Loss: 2.5664
Epoch 1/10... Discr. Loss: 0.9363... Generator Loss: 1.5580
Epoch 1/10... Discr. Loss: 0.8437... Generator Loss: 1.3878
Epoch 1/10... Discr. Loss: 1.2916... Generator Loss: 0.8139
Epoch 1/10... Discr. Loss: 1.0162... Generator Loss: 1.2366
Epoch 1/10... Discr. Loss: 0.7281... Generator Loss: 1.5461
Epoch 1/10... Discr. Loss: 1.1118... Generator Loss: 2.3392
Epoch 1/10... Discr. Loss: 1.8572... Generator Loss: 2.7279
Epoch 1/10... Discr. Loss: 1.0576... Generator Loss: 1.0714
Epoch 1/10... Discr. Loss: 0.9880... Generator Loss: 1.1238
Epoch 1/10... Discr. Loss: 1.4067... Generator Loss: 0.7466
Epoch 1/10... Discr. Loss: 0.9980... Generator Loss: 1.8130
Epoch 1/10... Discr. Loss: 0.9752... Generator Loss: 2.1135
Epoch 1/10... Discr. Loss: 1.0875... Generator Loss: 1.3689
Epoch 1/10... Discr. Loss: 1.0619... Generator Loss: 1.1356
Epoch 1/10... Discr. Loss: 1.2650... Generator Loss: 2.0612
Epoch 1/10... Discr. Loss: 1.0926... Generator Loss: 1.2863
Epoch 1/10... Discr. Loss: 1.3173... Generator Loss: 1.3200
Epoch 1/10... Discr. Loss: 1.0152... Generator Loss: 1.8613
Epoch 1/10... Discr. Loss: 0.9908... Generator Loss: 1.2356
Epoch 1/10... Discr. Loss: 1.0371... Generator Loss: 1.0388
Epoch 1/10... Discr. Loss: 0.8551... Generator Loss: 1.7915
Epoch 1/10... Discr. Loss: 1.2190... Generator Loss: 0.7403
Epoch 1/10... Discr. Loss: 1.1487... Generator Loss: 1.5626
Epoch 1/10... Discr. Loss: 1.2148... Generator Loss: 2.1392
Epoch 1/10... Discr. Loss: 0.8896... Generator Loss: 1.5533
Epoch 1/10... Discr. Loss: 1.1545... Generator Loss: 0.9298
Epoch 1/10... Discr. Loss: 1.2073... Generator Loss: 0.8083
Epoch 1/10... Discr. Loss: 1.0937... Generator Loss: 1.2028
Epoch 1/10... Discr. Loss: 1.2000... Generator Loss: 1.1890
Epoch 1/10... Discr. Loss: 1.5628... Generator Loss: 0.7697
Epoch 1/10... Discr. Loss: 1.3221... Generator Loss: 1.0965
Epoch 1/10... Discr. Loss: 1.0137... Generator Loss: 1.5697
Epoch 1/10... Discr. Loss: 1.0410... Generator Loss: 1.3465
Epoch 1/10... Discr. Loss: 1.1514... Generator Loss: 1.3825
Epoch 1/10... Discr. Loss: 1.1036... Generator Loss: 1.1055
Epoch 1/10... Discr. Loss: 0.9221... Generator Loss: 1.3833
Epoch 1/10... Discr. Loss: 0.8993... Generator Loss: 1.2987
Epoch 1/10... Discr. Loss: 1.1261... Generator Loss: 1.8109
Epoch 1/10... Discr. Loss: 0.9237... Generator Loss: 1.5087
Epoch 1/10... Discr. Loss: 1.0539... Generator Loss: 1.3063
Epoch 1/10... Discr. Loss: 0.9920... Generator Loss: 1.3332
Epoch 1/10... Discr. Loss: 1.1550... Generator Loss: 0.8570
Epoch 1/10... Discr. Loss: 0.8813... Generator Loss: 1.4262
Epoch 1/10... Discr. Loss: 1.4294... Generator Loss: 0.6716
Epoch 1/10... Discr. Loss: 1.2165... Generator Loss: 1.0804
Epoch 1/10... Discr. Loss: 1.0298... Generator Loss: 1.0155
Epoch 1/10... Discr. Loss: 1.1637... Generator Loss: 0.8693
Epoch 1/10... Discr. Loss: 1.2031... Generator Loss: 1.5342
Epoch 1/10... Discr. Loss: 1.1570... Generator Loss: 1.2829
Epoch 1/10... Discr. Loss: 1.0603... Generator Loss: 1.0586
Epoch 1/10... Discr. Loss: 1.0284... Generator Loss: 1.1892
Epoch 1/10... Discr. Loss: 0.9730... Generator Loss: 0.9904
Epoch 1/10... Discr. Loss: 1.1497... Generator Loss: 1.3605
Epoch 1/10... Discr. Loss: 1.5446... Generator Loss: 0.6091
Epoch 1/10... Discr. Loss: 1.1182... Generator Loss: 1.2302
Epoch 1/10... Discr. Loss: 0.9773... Generator Loss: 1.2188
Epoch 1/10... Discr. Loss: 1.1225... Generator Loss: 1.0511
Epoch 1/10... Discr. Loss: 0.8410... Generator Loss: 1.3534
Epoch 1/10... Discr. Loss: 1.2017... Generator Loss: 1.1884
Epoch 1/10... Discr. Loss: 1.0080... Generator Loss: 1.4102
Epoch 1/10... Discr. Loss: 0.9826... Generator Loss: 1.2279
Epoch 1/10... Discr. Loss: 0.9642... Generator Loss: 1.2111
Epoch 1/10... Discr. Loss: 0.9826... Generator Loss: 1.4459
Epoch 1/10... Discr. Loss: 1.1142... Generator Loss: 1.0470
Epoch 1/10... Discr. Loss: 1.1046... Generator Loss: 1.4054
Epoch 1/10... Discr. Loss: 0.9513... Generator Loss: 1.3825
Epoch 1/10... Discr. Loss: 1.1763... Generator Loss: 0.9368
Epoch 1/10... Discr. Loss: 1.1766... Generator Loss: 1.2256
Epoch 1/10... Discr. Loss: 1.1618... Generator Loss: 1.1118
Epoch 1/10... Discr. Loss: 1.1968... Generator Loss: 2.0154
Epoch 1/10... Discr. Loss: 0.9942... Generator Loss: 0.9885
Epoch 1/10... Discr. Loss: 1.2105... Generator Loss: 0.8886
Epoch 1/10... Discr. Loss: 1.0956... Generator Loss: 1.5011
Epoch 1/10... Discr. Loss: 1.1074... Generator Loss: 1.1476
Epoch 1/10... Discr. Loss: 1.1233... Generator Loss: 1.2571
Epoch 1/10... Discr. Loss: 1.2078... Generator Loss: 0.8894
Epoch 1/10... Discr. Loss: 1.1367... Generator Loss: 1.0467
Epoch 1/10... Discr. Loss: 1.3230... Generator Loss: 1.8696
Epoch 1/10... Discr. Loss: 0.9966... Generator Loss: 1.0342
Epoch 1/10... Discr. Loss: 1.0348... Generator Loss: 1.7304
Epoch 1/10... Discr. Loss: 1.1446... Generator Loss: 0.9921
Epoch 1/10... Discr. Loss: 1.0117... Generator Loss: 1.4493
Epoch 1/10... Discr. Loss: 1.0847... Generator Loss: 0.9217
Epoch 1/10... Discr. Loss: 1.1221... Generator Loss: 1.1396
Epoch 1/10... Discr. Loss: 1.0417... Generator Loss: 1.1617
Epoch 1/10... Discr. Loss: 1.2304... Generator Loss: 1.0515
Epoch 1/10... Discr. Loss: 1.0372... Generator Loss: 1.3336
Epoch 1/10... Discr. Loss: 1.0153... Generator Loss: 1.5759
Epoch 1/10... Discr. Loss: 1.1719... Generator Loss: 1.4962
Epoch 1/10... Discr. Loss: 0.9905... Generator Loss: 1.3734
Epoch 1/10... Discr. Loss: 0.9371... Generator Loss: 1.6909
Epoch 1/10... Discr. Loss: 1.0910... Generator Loss: 1.2619
Epoch 1/10... Discr. Loss: 1.0097... Generator Loss: 1.5880
Epoch 1/10... Discr. Loss: 0.8229... Generator Loss: 1.5186
Epoch 1/10... Discr. Loss: 0.9697... Generator Loss: 1.2166
Epoch 1/10... Discr. Loss: 0.9059... Generator Loss: 1.2320
Epoch 1/10... Discr. Loss: 1.0472... Generator Loss: 1.4835
Epoch 1/10... Discr. Loss: 1.0097... Generator Loss: 1.4140
Epoch 1/10... Discr. Loss: 0.9929... Generator Loss: 1.5871
Epoch 1/10... Discr. Loss: 1.1070... Generator Loss: 1.9457
Epoch 1/10... Discr. Loss: 0.9728... Generator Loss: 1.4930
Epoch 1/10... Discr. Loss: 1.0060... Generator Loss: 1.3365
Epoch 1/10... Discr. Loss: 1.0419... Generator Loss: 1.9276
Epoch 1/10... Discr. Loss: 1.0513... Generator Loss: 0.9889
Epoch 1/10... Discr. Loss: 0.9790... Generator Loss: 1.8107
Epoch 1/10... Discr. Loss: 0.9335... Generator Loss: 1.4132
Epoch 1/10... Discr. Loss: 1.1270... Generator Loss: 0.9602
Epoch 1/10... Discr. Loss: 1.0974... Generator Loss: 1.0055
Epoch 1/10... Discr. Loss: 1.0464... Generator Loss: 1.1374
Epoch 1/10... Discr. Loss: 0.9407... Generator Loss: 1.1842
Epoch 1/10... Discr. Loss: 1.2885... Generator Loss: 0.7422
Epoch 1/10... Discr. Loss: 0.9610... Generator Loss: 1.6595
Epoch 1/10... Discr. Loss: 1.0631... Generator Loss: 1.5724
Epoch 1/10... Discr. Loss: 1.2870... Generator Loss: 1.8009
Epoch 1/10... Discr. Loss: 1.0557... Generator Loss: 1.0660
Epoch 1/10... Discr. Loss: 1.0373... Generator Loss: 1.3927
Epoch 2/10... Discr. Loss: 1.0510... Generator Loss: 1.0045
Epoch 2/10... Discr. Loss: 1.0649... Generator Loss: 1.2853
Epoch 2/10... Discr. Loss: 1.0748... Generator Loss: 1.1192
Epoch 2/10... Discr. Loss: 0.9429... Generator Loss: 1.2390
Epoch 2/10... Discr. Loss: 1.0388... Generator Loss: 1.4487
Epoch 2/10... Discr. Loss: 1.2969... Generator Loss: 1.4282
Epoch 2/10... Discr. Loss: 0.9700... Generator Loss: 1.1832
Epoch 2/10... Discr. Loss: 0.9701... Generator Loss: 1.2490
Epoch 2/10... Discr. Loss: 1.0528... Generator Loss: 2.0672
Epoch 2/10... Discr. Loss: 0.9279... Generator Loss: 1.4082
Epoch 2/10... Discr. Loss: 1.2328... Generator Loss: 1.0466
Epoch 2/10... Discr. Loss: 2.0884... Generator Loss: 1.8350
Epoch 2/10... Discr. Loss: 1.0392... Generator Loss: 1.3618
Epoch 2/10... Discr. Loss: 0.9832... Generator Loss: 1.5456
Epoch 2/10... Discr. Loss: 1.0360... Generator Loss: 1.1362
Epoch 2/10... Discr. Loss: 0.9774... Generator Loss: 1.3468
Epoch 2/10... Discr. Loss: 0.9571... Generator Loss: 1.3551
Epoch 2/10... Discr. Loss: 1.1861... Generator Loss: 0.8013
Epoch 2/10... Discr. Loss: 1.1558... Generator Loss: 1.0974
Epoch 2/10... Discr. Loss: 0.9548... Generator Loss: 1.0660
Epoch 2/10... Discr. Loss: 1.0276... Generator Loss: 1.2231
Epoch 2/10... Discr. Loss: 0.9719... Generator Loss: 1.1554
Epoch 2/10... Discr. Loss: 1.0632... Generator Loss: 1.6286
Epoch 2/10... Discr. Loss: 1.0586... Generator Loss: 1.0096
Epoch 2/10... Discr. Loss: 1.0944... Generator Loss: 1.3423
Epoch 2/10... Discr. Loss: 1.0337... Generator Loss: 1.2487
Epoch 2/10... Discr. Loss: 1.0199... Generator Loss: 1.2820
Epoch 2/10... Discr. Loss: 0.9763... Generator Loss: 1.3895
Epoch 2/10... Discr. Loss: 1.0253... Generator Loss: 1.5729
Epoch 2/10... Discr. Loss: 1.0507... Generator Loss: 0.9569
Epoch 2/10... Discr. Loss: 1.0511... Generator Loss: 1.1925
Epoch 2/10... Discr. Loss: 0.9436... Generator Loss: 1.5517
Epoch 2/10... Discr. Loss: 1.0945... Generator Loss: 0.8276
Epoch 2/10... Discr. Loss: 1.0455... Generator Loss: 0.9501
Epoch 2/10... Discr. Loss: 1.0419... Generator Loss: 1.3857
Epoch 2/10... Discr. Loss: 0.8994... Generator Loss: 1.3970
Epoch 2/10... Discr. Loss: 0.9608... Generator Loss: 1.0767
Epoch 2/10... Discr. Loss: 1.0702... Generator Loss: 1.7198
Epoch 2/10... Discr. Loss: 1.1830... Generator Loss: 0.8446
Epoch 2/10... Discr. Loss: 1.0595... Generator Loss: 1.3250
Epoch 2/10... Discr. Loss: 0.9256... Generator Loss: 1.6188
Epoch 2/10... Discr. Loss: 0.9389... Generator Loss: 1.3309
Epoch 2/10... Discr. Loss: 1.0105... Generator Loss: 1.6806
Epoch 2/10... Discr. Loss: 1.2425... Generator Loss: 1.9753
Epoch 2/10... Discr. Loss: 1.1661... Generator Loss: 1.4918
Epoch 2/10... Discr. Loss: 1.0173... Generator Loss: 1.3854
Epoch 2/10... Discr. Loss: 1.1117... Generator Loss: 0.8319
Epoch 2/10... Discr. Loss: 1.0135... Generator Loss: 1.0288
Epoch 2/10... Discr. Loss: 0.9959... Generator Loss: 1.2063
Epoch 2/10... Discr. Loss: 0.9561... Generator Loss: 1.1227
Epoch 2/10... Discr. Loss: 1.8610... Generator Loss: 0.3877
Epoch 2/10... Discr. Loss: 1.0106... Generator Loss: 1.1446
Epoch 2/10... Discr. Loss: 0.9255... Generator Loss: 1.3428
Epoch 2/10... Discr. Loss: 1.0765... Generator Loss: 0.8452
Epoch 2/10... Discr. Loss: 1.0212... Generator Loss: 1.0180
Epoch 2/10... Discr. Loss: 1.2831... Generator Loss: 0.6565
Epoch 2/10... Discr. Loss: 0.8673... Generator Loss: 1.3810
Epoch 2/10... Discr. Loss: 1.5010... Generator Loss: 0.5412
Epoch 2/10... Discr. Loss: 1.0269... Generator Loss: 1.1206
Epoch 2/10... Discr. Loss: 1.0585... Generator Loss: 1.4795
Epoch 2/10... Discr. Loss: 1.0373... Generator Loss: 1.6897
Epoch 2/10... Discr. Loss: 1.0949... Generator Loss: 1.8189
Epoch 2/10... Discr. Loss: 1.0825... Generator Loss: 0.9511
Epoch 2/10... Discr. Loss: 2.0932... Generator Loss: 1.5080
Epoch 2/10... Discr. Loss: 0.9925... Generator Loss: 1.2610
Epoch 2/10... Discr. Loss: 0.9914... Generator Loss: 1.2777
Epoch 2/10... Discr. Loss: 0.9568... Generator Loss: 1.2421
Epoch 2/10... Discr. Loss: 1.0392... Generator Loss: 1.0988
Epoch 2/10... Discr. Loss: 0.9612... Generator Loss: 1.1191
Epoch 2/10... Discr. Loss: 1.0074... Generator Loss: 1.4417
Epoch 2/10... Discr. Loss: 1.5830... Generator Loss: 2.4363
Epoch 2/10... Discr. Loss: 0.9574... Generator Loss: 1.4526
Epoch 2/10... Discr. Loss: 1.0035... Generator Loss: 1.2720
Epoch 2/10... Discr. Loss: 1.0218... Generator Loss: 1.2181
Epoch 2/10... Discr. Loss: 0.9888... Generator Loss: 1.5265
Epoch 2/10... Discr. Loss: 1.0757... Generator Loss: 1.4572
Epoch 2/10... Discr. Loss: 1.0363... Generator Loss: 1.3473
Epoch 2/10... Discr. Loss: 1.1484... Generator Loss: 1.7516
Epoch 2/10... Discr. Loss: 1.0547... Generator Loss: 1.3299
Epoch 2/10... Discr. Loss: 0.9856... Generator Loss: 1.6162
Epoch 2/10... Discr. Loss: 1.0741... Generator Loss: 1.1472
Epoch 2/10... Discr. Loss: 0.9035... Generator Loss: 1.4113
Epoch 2/10... Discr. Loss: 1.0379... Generator Loss: 1.1202
Epoch 2/10... Discr. Loss: 1.2425... Generator Loss: 0.7486
Epoch 2/10... Discr. Loss: 1.1172... Generator Loss: 1.4724
Epoch 2/10... Discr. Loss: 1.0521... Generator Loss: 1.2802
Epoch 2/10... Discr. Loss: 1.1473... Generator Loss: 1.2908
Epoch 2/10... Discr. Loss: 1.0308... Generator Loss: 1.0587
Epoch 2/10... Discr. Loss: 1.0437... Generator Loss: 1.0856
Epoch 2/10... Discr. Loss: 1.0528... Generator Loss: 1.1603
Epoch 2/10... Discr. Loss: 1.0047... Generator Loss: 1.7749
Epoch 2/10... Discr. Loss: 1.1370... Generator Loss: 0.9973
Epoch 2/10... Discr. Loss: 1.0897... Generator Loss: 1.0913
Epoch 2/10... Discr. Loss: 1.1684... Generator Loss: 0.9192
Epoch 2/10... Discr. Loss: 0.9842... Generator Loss: 1.1892
Epoch 2/10... Discr. Loss: 0.9672... Generator Loss: 1.3747
Epoch 2/10... Discr. Loss: 1.0400... Generator Loss: 1.2896
Epoch 2/10... Discr. Loss: 1.1146... Generator Loss: 0.9824
Epoch 2/10... Discr. Loss: 1.1765... Generator Loss: 0.7859
Epoch 2/10... Discr. Loss: 1.1901... Generator Loss: 1.7743
Epoch 2/10... Discr. Loss: 1.0804... Generator Loss: 1.0451
Epoch 2/10... Discr. Loss: 1.0087... Generator Loss: 1.2733
Epoch 2/10... Discr. Loss: 0.9712... Generator Loss: 1.3127
Epoch 2/10... Discr. Loss: 1.1529... Generator Loss: 1.2995
Epoch 2/10... Discr. Loss: 0.9900... Generator Loss: 1.0834
Epoch 2/10... Discr. Loss: 1.3567... Generator Loss: 0.6514
Epoch 2/10... Discr. Loss: 1.0688... Generator Loss: 1.2612
Epoch 2/10... Discr. Loss: 1.0081... Generator Loss: 1.1942
Epoch 2/10... Discr. Loss: 0.9857... Generator Loss: 1.2880
Epoch 2/10... Discr. Loss: 1.1606... Generator Loss: 1.4990
Epoch 2/10... Discr. Loss: 1.0696... Generator Loss: 0.9475
Epoch 2/10... Discr. Loss: 0.8949... Generator Loss: 1.4591
Epoch 2/10... Discr. Loss: 1.0990... Generator Loss: 1.3566
Epoch 2/10... Discr. Loss: 1.0427... Generator Loss: 1.1688
Epoch 2/10... Discr. Loss: 1.2534... Generator Loss: 1.6031
Epoch 2/10... Discr. Loss: 1.0675... Generator Loss: 1.1877
Epoch 2/10... Discr. Loss: 1.1745... Generator Loss: 1.7819
Epoch 2/10... Discr. Loss: 1.0497... Generator Loss: 1.2817
Epoch 2/10... Discr. Loss: 1.0922... Generator Loss: 1.1683
Epoch 2/10... Discr. Loss: 1.0238... Generator Loss: 1.7329
Epoch 2/10... Discr. Loss: 1.0552... Generator Loss: 1.1841
Epoch 2/10... Discr. Loss: 1.0494... Generator Loss: 1.2616
Epoch 2/10... Discr. Loss: 1.0591... Generator Loss: 1.4264
Epoch 2/10... Discr. Loss: 1.3682... Generator Loss: 0.6473
Epoch 2/10... Discr. Loss: 1.0416... Generator Loss: 1.4539
Epoch 2/10... Discr. Loss: 1.1715... Generator Loss: 0.8247
Epoch 2/10... Discr. Loss: 1.3064... Generator Loss: 0.7216
Epoch 2/10... Discr. Loss: 1.0793... Generator Loss: 1.6409
Epoch 2/10... Discr. Loss: 1.0051... Generator Loss: 1.4276
Epoch 2/10... Discr. Loss: 1.0667... Generator Loss: 1.1575
Epoch 2/10... Discr. Loss: 1.0128... Generator Loss: 1.1620
Epoch 2/10... Discr. Loss: 1.0120... Generator Loss: 1.4125
Epoch 2/10... Discr. Loss: 1.1258... Generator Loss: 1.5173
Epoch 2/10... Discr. Loss: 0.9976... Generator Loss: 1.4225
Epoch 2/10... Discr. Loss: 1.1198... Generator Loss: 0.9484
Epoch 2/10... Discr. Loss: 1.1058... Generator Loss: 1.2048
Epoch 2/10... Discr. Loss: 1.2352... Generator Loss: 0.7059
Epoch 2/10... Discr. Loss: 1.0665... Generator Loss: 1.0332
Epoch 2/10... Discr. Loss: 1.1618... Generator Loss: 1.7585
Epoch 2/10... Discr. Loss: 1.0219... Generator Loss: 1.2369
Epoch 2/10... Discr. Loss: 1.0260... Generator Loss: 1.2109
Epoch 2/10... Discr. Loss: 1.0290... Generator Loss: 1.4409
Epoch 2/10... Discr. Loss: 1.1392... Generator Loss: 1.4729
Epoch 2/10... Discr. Loss: 1.4349... Generator Loss: 2.2492
Epoch 2/10... Discr. Loss: 1.1079... Generator Loss: 1.1814
Epoch 2/10... Discr. Loss: 1.0411... Generator Loss: 1.3732
Epoch 2/10... Discr. Loss: 1.0144... Generator Loss: 1.1871
Epoch 2/10... Discr. Loss: 1.4238... Generator Loss: 2.2467
Epoch 2/10... Discr. Loss: 1.0940... Generator Loss: 1.0681
Epoch 2/10... Discr. Loss: 1.0931... Generator Loss: 1.3256
Epoch 2/10... Discr. Loss: 1.0512... Generator Loss: 1.1261
Epoch 2/10... Discr. Loss: 0.9687... Generator Loss: 1.3911
Epoch 2/10... Discr. Loss: 1.0850... Generator Loss: 1.2698
Epoch 2/10... Discr. Loss: 1.1193... Generator Loss: 0.9348
Epoch 2/10... Discr. Loss: 0.9593... Generator Loss: 1.6210
Epoch 2/10... Discr. Loss: 1.8946... Generator Loss: 0.9438
Epoch 2/10... Discr. Loss: 1.1671... Generator Loss: 1.3944
Epoch 2/10... Discr. Loss: 0.9746... Generator Loss: 1.2508
Epoch 3/10... Discr. Loss: 1.1750... Generator Loss: 0.9334
Epoch 3/10... Discr. Loss: 1.0287... Generator Loss: 1.4984
Epoch 3/10... Discr. Loss: 1.0981... Generator Loss: 1.1779
Epoch 3/10... Discr. Loss: 1.0280... Generator Loss: 1.3476
Epoch 3/10... Discr. Loss: 1.1705... Generator Loss: 1.3019
Epoch 3/10... Discr. Loss: 1.1095... Generator Loss: 1.2871
Epoch 3/10... Discr. Loss: 1.2030... Generator Loss: 0.8233
Epoch 3/10... Discr. Loss: 1.1388... Generator Loss: 0.9678
Epoch 3/10... Discr. Loss: 1.0708... Generator Loss: 1.4792
Epoch 3/10... Discr. Loss: 1.0541... Generator Loss: 1.3573
Epoch 3/10... Discr. Loss: 1.0776... Generator Loss: 1.0943
Epoch 3/10... Discr. Loss: 1.1163... Generator Loss: 1.0305
Epoch 3/10... Discr. Loss: 1.1793... Generator Loss: 0.8609
Epoch 3/10... Discr. Loss: 1.0165... Generator Loss: 1.1431
Epoch 3/10... Discr. Loss: 1.1296... Generator Loss: 1.2508
Epoch 3/10... Discr. Loss: 1.1082... Generator Loss: 0.9663
Epoch 3/10... Discr. Loss: 1.2592... Generator Loss: 0.9060
Epoch 3/10... Discr. Loss: 1.2266... Generator Loss: 1.2261
Epoch 3/10... Discr. Loss: 1.1469... Generator Loss: 0.8486
Epoch 3/10... Discr. Loss: 1.1246... Generator Loss: 1.1460
Epoch 3/10... Discr. Loss: 1.0264... Generator Loss: 1.3212
Epoch 3/10... Discr. Loss: 1.0649... Generator Loss: 1.3565
Epoch 3/10... Discr. Loss: 1.0996... Generator Loss: 1.0762
Epoch 3/10... Discr. Loss: 1.0520... Generator Loss: 1.0626
Epoch 3/10... Discr. Loss: 1.0616... Generator Loss: 1.3013
Epoch 3/10... Discr. Loss: 1.1434... Generator Loss: 1.4211
Epoch 3/10... Discr. Loss: 1.1751... Generator Loss: 0.8366
Epoch 3/10... Discr. Loss: 1.1671... Generator Loss: 1.4485
Epoch 3/10... Discr. Loss: 1.3355... Generator Loss: 2.0730
Epoch 3/10... Discr. Loss: 1.0856... Generator Loss: 1.1760
Epoch 3/10... Discr. Loss: 1.0250... Generator Loss: 1.0565
Epoch 3/10... Discr. Loss: 1.1144... Generator Loss: 1.2587
Epoch 3/10... Discr. Loss: 1.1432... Generator Loss: 0.9966
Epoch 3/10... Discr. Loss: 1.0970... Generator Loss: 1.2615
Epoch 3/10... Discr. Loss: 1.0789... Generator Loss: 1.5153
Epoch 3/10... Discr. Loss: 1.0458... Generator Loss: 1.2065
Epoch 3/10... Discr. Loss: 1.0137... Generator Loss: 1.1503
Epoch 3/10... Discr. Loss: 1.2189... Generator Loss: 0.8600
Epoch 3/10... Discr. Loss: 1.0588... Generator Loss: 1.2330
Epoch 3/10... Discr. Loss: 1.2045... Generator Loss: 0.8112
Epoch 3/10... Discr. Loss: 1.0843... Generator Loss: 1.0298
Epoch 3/10... Discr. Loss: 1.2515... Generator Loss: 0.7985
Epoch 3/10... Discr. Loss: 1.0560... Generator Loss: 1.1182
Epoch 3/10... Discr. Loss: 1.0537... Generator Loss: 1.0927
Epoch 3/10... Discr. Loss: 1.0939... Generator Loss: 1.5994
Epoch 3/10... Discr. Loss: 1.1587... Generator Loss: 0.8798
Epoch 3/10... Discr. Loss: 1.1294... Generator Loss: 1.0436
Epoch 3/10... Discr. Loss: 1.0846... Generator Loss: 1.5576
Epoch 3/10... Discr. Loss: 1.2251... Generator Loss: 0.9636
Epoch 3/10... Discr. Loss: 1.1141... Generator Loss: 1.1714
Epoch 3/10... Discr. Loss: 1.1289... Generator Loss: 1.0480
Epoch 3/10... Discr. Loss: 1.2254... Generator Loss: 1.2215
Epoch 3/10... Discr. Loss: 1.0941... Generator Loss: 1.0096
Epoch 3/10... Discr. Loss: 1.1594... Generator Loss: 1.0645
Epoch 3/10... Discr. Loss: 1.1300... Generator Loss: 1.1518
Epoch 3/10... Discr. Loss: 1.7702... Generator Loss: 1.7547
Epoch 3/10... Discr. Loss: 1.1271... Generator Loss: 1.1074
Epoch 3/10... Discr. Loss: 1.1125... Generator Loss: 1.1015
Epoch 3/10... Discr. Loss: 1.0518... Generator Loss: 1.0129
Epoch 3/10... Discr. Loss: 1.0808... Generator Loss: 1.0436
Epoch 3/10... Discr. Loss: 1.0645... Generator Loss: 1.1753
Epoch 3/10... Discr. Loss: 1.0566... Generator Loss: 1.2748
Epoch 3/10... Discr. Loss: 1.0797... Generator Loss: 1.0316
Epoch 3/10... Discr. Loss: 1.5600... Generator Loss: 0.5267
Epoch 3/10... Discr. Loss: 1.0993... Generator Loss: 1.0956
Epoch 3/10... Discr. Loss: 1.0916... Generator Loss: 1.1671
Epoch 3/10... Discr. Loss: 1.1353... Generator Loss: 1.1751
Epoch 3/10... Discr. Loss: 1.0944... Generator Loss: 0.9468
Epoch 3/10... Discr. Loss: 1.1135... Generator Loss: 1.3332
Epoch 3/10... Discr. Loss: 1.0708... Generator Loss: 1.3980
Epoch 3/10... Discr. Loss: 1.1539... Generator Loss: 1.0759
Epoch 3/10... Discr. Loss: 1.3240... Generator Loss: 2.0008
Epoch 3/10... Discr. Loss: 1.1129... Generator Loss: 1.0405
Epoch 3/10... Discr. Loss: 1.4208... Generator Loss: 0.6588
Epoch 3/10... Discr. Loss: 1.0817... Generator Loss: 1.0461
Epoch 3/10... Discr. Loss: 1.0989... Generator Loss: 1.2077
Epoch 3/10... Discr. Loss: 1.2346... Generator Loss: 0.7911
Epoch 3/10... Discr. Loss: 1.0943... Generator Loss: 1.2473
Epoch 3/10... Discr. Loss: 1.0868... Generator Loss: 1.2056
Epoch 3/10... Discr. Loss: 1.0957... Generator Loss: 1.0609
Epoch 3/10... Discr. Loss: 1.0869... Generator Loss: 1.2462
Epoch 3/10... Discr. Loss: 1.0268... Generator Loss: 1.3479
Epoch 3/10... Discr. Loss: 1.1188... Generator Loss: 0.9348
Epoch 3/10... Discr. Loss: 1.1178... Generator Loss: 1.1388
Epoch 3/10... Discr. Loss: 1.0692... Generator Loss: 1.4534
Epoch 3/10... Discr. Loss: 1.9106... Generator Loss: 1.8354
Epoch 3/10... Discr. Loss: 1.2913... Generator Loss: 1.2081
Epoch 3/10... Discr. Loss: 1.1802... Generator Loss: 0.9197
Epoch 3/10... Discr. Loss: 1.0918... Generator Loss: 1.2950
Epoch 3/10... Discr. Loss: 1.1571... Generator Loss: 1.0527
Epoch 3/10... Discr. Loss: 1.1603... Generator Loss: 1.1950
Epoch 3/10... Discr. Loss: 1.1508... Generator Loss: 1.1422
Epoch 3/10... Discr. Loss: 1.0531... Generator Loss: 1.1267
Epoch 3/10... Discr. Loss: 1.0746... Generator Loss: 1.4342
Epoch 3/10... Discr. Loss: 1.0475... Generator Loss: 1.1565
Epoch 3/10... Discr. Loss: 1.0301... Generator Loss: 1.1506
Epoch 3/10... Discr. Loss: 1.3626... Generator Loss: 0.5876
Epoch 3/10... Discr. Loss: 1.3664... Generator Loss: 1.6205
Epoch 3/10... Discr. Loss: 1.1080... Generator Loss: 0.9703
Epoch 3/10... Discr. Loss: 1.2071... Generator Loss: 0.8583
Epoch 3/10... Discr. Loss: 1.0241... Generator Loss: 1.2243
Epoch 3/10... Discr. Loss: 1.0248... Generator Loss: 1.3942
Epoch 3/10... Discr. Loss: 1.0850... Generator Loss: 1.0610
Epoch 3/10... Discr. Loss: 1.0931... Generator Loss: 1.1892
Epoch 3/10... Discr. Loss: 1.0984... Generator Loss: 1.3244
Epoch 3/10... Discr. Loss: 1.2845... Generator Loss: 0.7018
Epoch 3/10... Discr. Loss: 1.0997... Generator Loss: 1.0977
Epoch 3/10... Discr. Loss: 1.1034... Generator Loss: 1.0310
Epoch 3/10... Discr. Loss: 1.0968... Generator Loss: 1.1281
Epoch 3/10... Discr. Loss: 1.1955... Generator Loss: 0.7453
Epoch 3/10... Discr. Loss: 1.0773... Generator Loss: 1.1987
Epoch 3/10... Discr. Loss: 1.0924... Generator Loss: 1.3060
Epoch 3/10... Discr. Loss: 1.0951... Generator Loss: 1.2755
Epoch 3/10... Discr. Loss: 1.1402... Generator Loss: 1.1390
Epoch 3/10... Discr. Loss: 1.0933... Generator Loss: 1.3319
Epoch 3/10... Discr. Loss: 1.1495... Generator Loss: 1.4498
Epoch 3/10... Discr. Loss: 1.1396... Generator Loss: 1.2475
Epoch 3/10... Discr. Loss: 1.0272... Generator Loss: 1.2426
Epoch 3/10... Discr. Loss: 1.2795... Generator Loss: 1.3444
Epoch 3/10... Discr. Loss: 1.0852... Generator Loss: 1.4241
Epoch 3/10... Discr. Loss: 1.1749... Generator Loss: 0.9542
Epoch 3/10... Discr. Loss: 1.2421... Generator Loss: 0.7312
Epoch 3/10... Discr. Loss: 1.2184... Generator Loss: 0.8152
Epoch 3/10... Discr. Loss: 1.0720... Generator Loss: 1.2978
Epoch 3/10... Discr. Loss: 1.0191... Generator Loss: 1.6021
Epoch 3/10... Discr. Loss: 1.2532... Generator Loss: 1.1530
Epoch 3/10... Discr. Loss: 1.1369... Generator Loss: 1.0816
Epoch 3/10... Discr. Loss: 1.1283... Generator Loss: 1.0608
Epoch 3/10... Discr. Loss: 1.5375... Generator Loss: 0.4950
Epoch 3/10... Discr. Loss: 1.0866... Generator Loss: 1.1477
Epoch 3/10... Discr. Loss: 1.1167... Generator Loss: 1.4449
Epoch 3/10... Discr. Loss: 1.1204... Generator Loss: 1.1158
Epoch 3/10... Discr. Loss: 1.0973... Generator Loss: 1.0879
Epoch 3/10... Discr. Loss: 1.1736... Generator Loss: 1.1305
Epoch 3/10... Discr. Loss: 1.1421... Generator Loss: 0.9147
Epoch 3/10... Discr. Loss: 1.1122... Generator Loss: 1.4513
Epoch 3/10... Discr. Loss: 1.2938... Generator Loss: 1.2310
Epoch 3/10... Discr. Loss: 1.0586... Generator Loss: 1.2561
Epoch 3/10... Discr. Loss: 1.2852... Generator Loss: 1.7612
Epoch 3/10... Discr. Loss: 1.1682... Generator Loss: 1.2440
Epoch 3/10... Discr. Loss: 1.2170... Generator Loss: 1.7811
Epoch 3/10... Discr. Loss: 1.1429... Generator Loss: 0.9390
Epoch 3/10... Discr. Loss: 1.1910... Generator Loss: 0.8761
Epoch 3/10... Discr. Loss: 1.2818... Generator Loss: 0.7527
Epoch 3/10... Discr. Loss: 1.1565... Generator Loss: 1.1740
Epoch 3/10... Discr. Loss: 1.2887... Generator Loss: 0.6502
Epoch 3/10... Discr. Loss: 1.0859... Generator Loss: 1.1026
Epoch 3/10... Discr. Loss: 1.0934... Generator Loss: 1.2816
Epoch 3/10... Discr. Loss: 1.1073... Generator Loss: 1.1035
Epoch 3/10... Discr. Loss: 1.0571... Generator Loss: 1.1952
Epoch 3/10... Discr. Loss: 1.0040... Generator Loss: 1.2341
Epoch 3/10... Discr. Loss: 1.6202... Generator Loss: 1.3152
Epoch 3/10... Discr. Loss: 1.1912... Generator Loss: 1.0110
Epoch 3/10... Discr. Loss: 1.2064... Generator Loss: 0.8827
Epoch 3/10... Discr. Loss: 1.0940... Generator Loss: 1.1241
Epoch 3/10... Discr. Loss: 1.1055... Generator Loss: 1.0686
Epoch 3/10... Discr. Loss: 1.0701... Generator Loss: 1.1181
Epoch 3/10... Discr. Loss: 1.0967... Generator Loss: 1.0492
Epoch 4/10... Discr. Loss: 1.0829... Generator Loss: 1.1656
Epoch 4/10... Discr. Loss: 1.1768... Generator Loss: 1.6113
Epoch 4/10... Discr. Loss: 1.0407... Generator Loss: 1.2063
Epoch 4/10... Discr. Loss: 1.0162... Generator Loss: 1.3607
Epoch 4/10... Discr. Loss: 1.1988... Generator Loss: 0.8769
Epoch 4/10... Discr. Loss: 1.1080... Generator Loss: 0.9268
Epoch 4/10... Discr. Loss: 1.1026... Generator Loss: 1.2747
Epoch 4/10... Discr. Loss: 1.6610... Generator Loss: 2.0960
Epoch 4/10... Discr. Loss: 1.1006... Generator Loss: 1.2544
Epoch 4/10... Discr. Loss: 1.1385... Generator Loss: 1.2734
Epoch 4/10... Discr. Loss: 1.3512... Generator Loss: 0.6687
Epoch 4/10... Discr. Loss: 1.1249... Generator Loss: 1.1099
Epoch 4/10... Discr. Loss: 1.0244... Generator Loss: 1.1786
Epoch 4/10... Discr. Loss: 1.1318... Generator Loss: 0.9701
Epoch 4/10... Discr. Loss: 0.9522... Generator Loss: 1.3047
Epoch 4/10... Discr. Loss: 1.1039... Generator Loss: 1.0035
Epoch 4/10... Discr. Loss: 1.0898... Generator Loss: 1.0482
Epoch 4/10... Discr. Loss: 1.3385... Generator Loss: 0.6173
Epoch 4/10... Discr. Loss: 1.1044... Generator Loss: 1.2304
Epoch 4/10... Discr. Loss: 1.1411... Generator Loss: 0.9361
Epoch 4/10... Discr. Loss: 1.0712... Generator Loss: 1.5275
Epoch 4/10... Discr. Loss: 1.2150... Generator Loss: 1.6418
Epoch 4/10... Discr. Loss: 1.1259... Generator Loss: 1.1170
Epoch 4/10... Discr. Loss: 1.1439... Generator Loss: 1.0350
Epoch 4/10... Discr. Loss: 1.2516... Generator Loss: 0.9686
Epoch 4/10... Discr. Loss: 1.0127... Generator Loss: 1.2741
Epoch 4/10... Discr. Loss: 1.2987... Generator Loss: 0.7499
Epoch 4/10... Discr. Loss: 1.1040... Generator Loss: 1.1056
Epoch 4/10... Discr. Loss: 0.9837... Generator Loss: 1.1974
Epoch 4/10... Discr. Loss: 1.1481... Generator Loss: 0.9704
Epoch 4/10... Discr. Loss: 1.1170... Generator Loss: 1.0044
Epoch 4/10... Discr. Loss: 1.0457... Generator Loss: 1.0111
Epoch 4/10... Discr. Loss: 1.0423... Generator Loss: 1.1166
Epoch 4/10... Discr. Loss: 1.2795... Generator Loss: 1.0018
Epoch 4/10... Discr. Loss: 1.0854... Generator Loss: 1.1337
Epoch 4/10... Discr. Loss: 1.7758... Generator Loss: 1.1821
Epoch 4/10... Discr. Loss: 1.1793... Generator Loss: 1.1512
Epoch 4/10... Discr. Loss: 1.1571... Generator Loss: 0.9463
Epoch 4/10... Discr. Loss: 1.1107... Generator Loss: 1.0246
Epoch 4/10... Discr. Loss: 1.0579... Generator Loss: 1.2204
Epoch 4/10... Discr. Loss: 1.0899... Generator Loss: 0.9457
Epoch 4/10... Discr. Loss: 1.0461... Generator Loss: 1.3159
Epoch 4/10... Discr. Loss: 1.0547... Generator Loss: 1.0937
Epoch 4/10... Discr. Loss: 0.9919... Generator Loss: 1.1861
Epoch 4/10... Discr. Loss: 1.2095... Generator Loss: 1.3611
Epoch 4/10... Discr. Loss: 1.0262... Generator Loss: 1.0986
Epoch 4/10... Discr. Loss: 1.2088... Generator Loss: 0.7730
Epoch 4/10... Discr. Loss: 1.1273... Generator Loss: 1.1036
Epoch 4/10... Discr. Loss: 1.1309... Generator Loss: 1.2131
Epoch 4/10... Discr. Loss: 1.0874... Generator Loss: 1.1188
Epoch 4/10... Discr. Loss: 1.0553... Generator Loss: 1.0513
Epoch 4/10... Discr. Loss: 1.0443... Generator Loss: 1.1761
Epoch 4/10... Discr. Loss: 1.0291... Generator Loss: 1.1646
Epoch 4/10... Discr. Loss: 1.1203... Generator Loss: 1.0361
Epoch 4/10... Discr. Loss: 1.1255... Generator Loss: 0.8990
Epoch 4/10... Discr. Loss: 1.1411... Generator Loss: 0.9085
Epoch 4/10... Discr. Loss: 1.1185... Generator Loss: 0.9223
Epoch 4/10... Discr. Loss: 1.0886... Generator Loss: 1.1018
Epoch 4/10... Discr. Loss: 1.0752... Generator Loss: 1.0006
Epoch 4/10... Discr. Loss: 1.0768... Generator Loss: 1.1230
Epoch 4/10... Discr. Loss: 1.0369... Generator Loss: 1.2943
Epoch 4/10... Discr. Loss: 1.0807... Generator Loss: 1.2221
Epoch 4/10... Discr. Loss: 1.0636... Generator Loss: 0.9991
Epoch 4/10... Discr. Loss: 1.2012... Generator Loss: 0.8331
Epoch 4/10... Discr. Loss: 1.1297... Generator Loss: 0.8997
Epoch 4/10... Discr. Loss: 1.1640... Generator Loss: 1.1239
Epoch 4/10... Discr. Loss: 1.1534... Generator Loss: 1.2455
Epoch 4/10... Discr. Loss: 1.2583... Generator Loss: 0.9801
Epoch 4/10... Discr. Loss: 1.0007... Generator Loss: 1.2928
Epoch 4/10... Discr. Loss: 1.1042... Generator Loss: 1.0229
Epoch 4/10... Discr. Loss: 1.0544... Generator Loss: 1.4065
Epoch 4/10... Discr. Loss: 1.0404... Generator Loss: 1.1567
Epoch 4/10... Discr. Loss: 1.1616... Generator Loss: 1.6179
Epoch 4/10... Discr. Loss: 1.1072... Generator Loss: 1.1052
Epoch 4/10... Discr. Loss: 1.4381... Generator Loss: 1.6172
Epoch 4/10... Discr. Loss: 1.1750... Generator Loss: 0.8866
Epoch 4/10... Discr. Loss: 1.6329... Generator Loss: 0.4308
Epoch 4/10... Discr. Loss: 1.0991... Generator Loss: 1.0744
Epoch 4/10... Discr. Loss: 1.0213... Generator Loss: 1.1491
Epoch 4/10... Discr. Loss: 0.9673... Generator Loss: 1.2458
Epoch 4/10... Discr. Loss: 1.1796... Generator Loss: 0.8715
Epoch 4/10... Discr. Loss: 1.1379... Generator Loss: 1.1369
Epoch 4/10... Discr. Loss: 1.0315... Generator Loss: 1.1031
Epoch 4/10... Discr. Loss: 1.0378... Generator Loss: 1.0962
Epoch 4/10... Discr. Loss: 1.2730... Generator Loss: 1.6736
Epoch 4/10... Discr. Loss: 1.2992... Generator Loss: 0.7070
Epoch 4/10... Discr. Loss: 1.0036... Generator Loss: 1.2295
Epoch 4/10... Discr. Loss: 0.9852... Generator Loss: 1.1269
Epoch 4/10... Discr. Loss: 0.9900... Generator Loss: 1.2996
Epoch 4/10... Discr. Loss: 1.0493... Generator Loss: 1.1379
Epoch 4/10... Discr. Loss: 1.0854... Generator Loss: 1.4392
Epoch 4/10... Discr. Loss: 1.1651... Generator Loss: 1.9172
Epoch 4/10... Discr. Loss: 1.1225... Generator Loss: 1.0176
Epoch 4/10... Discr. Loss: 1.0884... Generator Loss: 1.0775
Epoch 4/10... Discr. Loss: 1.1603... Generator Loss: 0.8880
Epoch 4/10... Discr. Loss: 1.1438... Generator Loss: 0.7575
Epoch 4/10... Discr. Loss: 1.0670... Generator Loss: 1.2199
Epoch 4/10... Discr. Loss: 1.1133... Generator Loss: 1.2270
Epoch 4/10... Discr. Loss: 1.2373... Generator Loss: 0.8129
Epoch 4/10... Discr. Loss: 0.9681... Generator Loss: 1.1527
Epoch 4/10... Discr. Loss: 1.3456... Generator Loss: 0.7037
Epoch 4/10... Discr. Loss: 1.0504... Generator Loss: 1.1809
Epoch 4/10... Discr. Loss: 1.0011... Generator Loss: 1.3380
Epoch 4/10... Discr. Loss: 1.1223... Generator Loss: 1.6918
Epoch 4/10... Discr. Loss: 1.2089... Generator Loss: 0.8350
Epoch 4/10... Discr. Loss: 1.0468... Generator Loss: 0.9776
Epoch 4/10... Discr. Loss: 1.1829... Generator Loss: 0.8374
Epoch 4/10... Discr. Loss: 1.1502... Generator Loss: 1.0157
Epoch 4/10... Discr. Loss: 0.9974... Generator Loss: 1.3118
Epoch 4/10... Discr. Loss: 0.9656... Generator Loss: 1.3570
Epoch 4/10... Discr. Loss: 1.5280... Generator Loss: 1.3571
Epoch 4/10... Discr. Loss: 1.0100... Generator Loss: 1.2878
Epoch 4/10... Discr. Loss: 0.9765... Generator Loss: 1.3099
Epoch 4/10... Discr. Loss: 1.0263... Generator Loss: 1.2457
Epoch 4/10... Discr. Loss: 0.9385... Generator Loss: 1.2046
Epoch 4/10... Discr. Loss: 0.9768... Generator Loss: 1.4556
Epoch 4/10... Discr. Loss: 1.1363... Generator Loss: 1.1824
Epoch 4/10... Discr. Loss: 1.0648... Generator Loss: 1.0447
Epoch 4/10... Discr. Loss: 1.0586... Generator Loss: 1.5281
Epoch 4/10... Discr. Loss: 1.3639... Generator Loss: 0.6642
Epoch 4/10... Discr. Loss: 1.2330... Generator Loss: 1.0817
Epoch 4/10... Discr. Loss: 1.0550... Generator Loss: 1.0110
Epoch 4/10... Discr. Loss: 1.0244... Generator Loss: 1.2797
Epoch 4/10... Discr. Loss: 1.0471... Generator Loss: 1.5649
Epoch 4/10... Discr. Loss: 1.0188... Generator Loss: 1.1770
Epoch 4/10... Discr. Loss: 1.0501... Generator Loss: 1.7636
Epoch 4/10... Discr. Loss: 1.0427... Generator Loss: 1.6261
Epoch 4/10... Discr. Loss: 0.9916... Generator Loss: 1.6227
Epoch 4/10... Discr. Loss: 1.3791... Generator Loss: 1.0598
Epoch 4/10... Discr. Loss: 1.0162... Generator Loss: 1.0758
Epoch 4/10... Discr. Loss: 0.9867... Generator Loss: 1.3912
Epoch 4/10... Discr. Loss: 1.0967... Generator Loss: 0.8676
Epoch 4/10... Discr. Loss: 1.4744... Generator Loss: 1.7475
Epoch 4/10... Discr. Loss: 1.1269... Generator Loss: 0.9396
Epoch 4/10... Discr. Loss: 0.9528... Generator Loss: 1.1539
Epoch 4/10... Discr. Loss: 1.0049... Generator Loss: 1.5719
Epoch 4/10... Discr. Loss: 1.2118... Generator Loss: 0.7056
Epoch 4/10... Discr. Loss: 1.0094... Generator Loss: 1.3474
Epoch 4/10... Discr. Loss: 1.1293... Generator Loss: 1.3998
Epoch 4/10... Discr. Loss: 1.1152... Generator Loss: 0.8678
Epoch 4/10... Discr. Loss: 0.9132... Generator Loss: 1.2421
Epoch 4/10... Discr. Loss: 1.1095... Generator Loss: 1.6905
Epoch 4/10... Discr. Loss: 1.3871... Generator Loss: 0.5532
Epoch 4/10... Discr. Loss: 1.2834... Generator Loss: 0.7191
Epoch 4/10... Discr. Loss: 1.0354... Generator Loss: 1.2180
Epoch 4/10... Discr. Loss: 1.0103... Generator Loss: 1.3917
Epoch 4/10... Discr. Loss: 1.0771... Generator Loss: 1.7941
Epoch 4/10... Discr. Loss: 1.0701... Generator Loss: 1.3306
Epoch 4/10... Discr. Loss: 1.1092... Generator Loss: 0.9086
Epoch 4/10... Discr. Loss: 1.0818... Generator Loss: 1.3813
Epoch 4/10... Discr. Loss: 1.4478... Generator Loss: 1.7142
Epoch 4/10... Discr. Loss: 1.1079... Generator Loss: 1.2757
Epoch 4/10... Discr. Loss: 0.9834... Generator Loss: 1.4039
Epoch 4/10... Discr. Loss: 0.9680... Generator Loss: 1.2593
Epoch 4/10... Discr. Loss: 1.0413... Generator Loss: 1.0565
Epoch 4/10... Discr. Loss: 0.9971... Generator Loss: 1.5838
Epoch 4/10... Discr. Loss: 1.0174... Generator Loss: 1.0943
Epoch 4/10... Discr. Loss: 1.0174... Generator Loss: 1.2686
Epoch 5/10... Discr. Loss: 0.9318... Generator Loss: 1.1917
Epoch 5/10... Discr. Loss: 0.8977... Generator Loss: 1.4366
Epoch 5/10... Discr. Loss: 1.0580... Generator Loss: 1.9614
Epoch 5/10... Discr. Loss: 0.9735... Generator Loss: 1.2075
Epoch 5/10... Discr. Loss: 1.8674... Generator Loss: 0.3217
Epoch 5/10... Discr. Loss: 1.2452... Generator Loss: 0.9088
Epoch 5/10... Discr. Loss: 1.0406... Generator Loss: 1.2293
Epoch 5/10... Discr. Loss: 1.0500... Generator Loss: 1.5883
Epoch 5/10... Discr. Loss: 0.9881... Generator Loss: 1.6606
Epoch 5/10... Discr. Loss: 1.0023... Generator Loss: 1.0504
Epoch 5/10... Discr. Loss: 1.0884... Generator Loss: 0.9610
Epoch 5/10... Discr. Loss: 0.9977... Generator Loss: 1.4230
Epoch 5/10... Discr. Loss: 0.9847... Generator Loss: 1.0698
Epoch 5/10... Discr. Loss: 1.0124... Generator Loss: 1.1631
Epoch 5/10... Discr. Loss: 1.1604... Generator Loss: 0.9872
Epoch 5/10... Discr. Loss: 1.4049... Generator Loss: 0.5874
Epoch 5/10... Discr. Loss: 1.1565... Generator Loss: 0.8934
Epoch 5/10... Discr. Loss: 1.2022... Generator Loss: 0.7551
Epoch 5/10... Discr. Loss: 0.9732... Generator Loss: 1.7722
Epoch 5/10... Discr. Loss: 1.0803... Generator Loss: 1.4233
Epoch 5/10... Discr. Loss: 0.9503... Generator Loss: 1.1757
Epoch 5/10... Discr. Loss: 1.0190... Generator Loss: 1.5355
Epoch 5/10... Discr. Loss: 0.8879... Generator Loss: 1.4336
Epoch 5/10... Discr. Loss: 1.0234... Generator Loss: 1.3756
Epoch 5/10... Discr. Loss: 1.2213... Generator Loss: 0.6807
Epoch 5/10... Discr. Loss: 1.0196... Generator Loss: 1.4493
Epoch 5/10... Discr. Loss: 0.9586... Generator Loss: 1.4346
Epoch 5/10... Discr. Loss: 1.0132... Generator Loss: 1.3066
Epoch 5/10... Discr. Loss: 0.9792... Generator Loss: 1.3197
Epoch 5/10... Discr. Loss: 1.0415... Generator Loss: 1.3803
Epoch 5/10... Discr. Loss: 1.2509... Generator Loss: 1.8932
Epoch 5/10... Discr. Loss: 0.9408... Generator Loss: 1.1506
Epoch 5/10... Discr. Loss: 0.9495... Generator Loss: 1.2016
Epoch 5/10... Discr. Loss: 1.3274... Generator Loss: 0.7178
Epoch 5/10... Discr. Loss: 0.9133... Generator Loss: 1.5354
Epoch 5/10... Discr. Loss: 0.9435... Generator Loss: 1.1322
Epoch 5/10... Discr. Loss: 1.1846... Generator Loss: 0.7698
Epoch 5/10... Discr. Loss: 1.3411... Generator Loss: 1.7536
Epoch 5/10... Discr. Loss: 0.9923... Generator Loss: 1.2858
Epoch 5/10... Discr. Loss: 0.9599... Generator Loss: 1.2223
Epoch 5/10... Discr. Loss: 1.0377... Generator Loss: 0.9527
Epoch 5/10... Discr. Loss: 0.9684... Generator Loss: 1.1339
Epoch 5/10... Discr. Loss: 0.9995... Generator Loss: 1.5401
Epoch 5/10... Discr. Loss: 1.1566... Generator Loss: 0.8238
Epoch 5/10... Discr. Loss: 1.0961... Generator Loss: 1.0220
Epoch 5/10... Discr. Loss: 0.9004... Generator Loss: 1.4705
Epoch 5/10... Discr. Loss: 1.0156... Generator Loss: 1.0753
Epoch 5/10... Discr. Loss: 0.9445... Generator Loss: 1.2079
Epoch 5/10... Discr. Loss: 1.0547... Generator Loss: 1.4283
Epoch 5/10... Discr. Loss: 1.6174... Generator Loss: 2.1206
Epoch 5/10... Discr. Loss: 1.5316... Generator Loss: 1.3535
Epoch 5/10... Discr. Loss: 1.0600... Generator Loss: 1.0454
Epoch 5/10... Discr. Loss: 1.0212... Generator Loss: 1.1875
Epoch 5/10... Discr. Loss: 0.9347... Generator Loss: 1.0744
Epoch 5/10... Discr. Loss: 1.1142... Generator Loss: 0.9943
Epoch 5/10... Discr. Loss: 1.0396... Generator Loss: 1.6153
Epoch 5/10... Discr. Loss: 0.9069... Generator Loss: 1.5174
Epoch 5/10... Discr. Loss: 0.9885... Generator Loss: 1.4978
Epoch 5/10... Discr. Loss: 0.9094... Generator Loss: 1.7304
Epoch 5/10... Discr. Loss: 1.5202... Generator Loss: 2.6362
Epoch 5/10... Discr. Loss: 1.1254... Generator Loss: 1.1019
Epoch 5/10... Discr. Loss: 1.2852... Generator Loss: 0.6732
Epoch 5/10... Discr. Loss: 0.9713... Generator Loss: 1.1026
Epoch 5/10... Discr. Loss: 1.1013... Generator Loss: 0.8805
Epoch 5/10... Discr. Loss: 0.9966... Generator Loss: 1.6931
Epoch 5/10... Discr. Loss: 1.0258... Generator Loss: 1.3587
Epoch 5/10... Discr. Loss: 0.8872... Generator Loss: 1.1717
Epoch 5/10... Discr. Loss: 1.0554... Generator Loss: 1.6602
Epoch 5/10... Discr. Loss: 0.9995... Generator Loss: 1.0884
Epoch 5/10... Discr. Loss: 0.8725... Generator Loss: 1.5051
Epoch 5/10... Discr. Loss: 0.9560... Generator Loss: 1.4730
Epoch 5/10... Discr. Loss: 0.9150... Generator Loss: 1.6224
Epoch 5/10... Discr. Loss: 1.0158... Generator Loss: 2.0080
Epoch 5/10... Discr. Loss: 0.9488... Generator Loss: 1.3300
Epoch 5/10... Discr. Loss: 1.5199... Generator Loss: 2.4073
Epoch 5/10... Discr. Loss: 1.3137... Generator Loss: 0.9812
Epoch 5/10... Discr. Loss: 0.9388... Generator Loss: 1.8485
Epoch 5/10... Discr. Loss: 0.8268... Generator Loss: 1.4681
Epoch 5/10... Discr. Loss: 0.9548... Generator Loss: 1.2589
Epoch 5/10... Discr. Loss: 0.8655... Generator Loss: 1.7636
Epoch 5/10... Discr. Loss: 0.9014... Generator Loss: 1.2981
Epoch 5/10... Discr. Loss: 1.2615... Generator Loss: 0.7246
Epoch 5/10... Discr. Loss: 1.0046... Generator Loss: 1.0996
Epoch 5/10... Discr. Loss: 1.0191... Generator Loss: 0.9554
Epoch 5/10... Discr. Loss: 1.0231... Generator Loss: 1.6925
Epoch 5/10... Discr. Loss: 0.9030... Generator Loss: 1.3446
Epoch 5/10... Discr. Loss: 0.9804... Generator Loss: 1.0308
Epoch 5/10... Discr. Loss: 0.9011... Generator Loss: 1.2572
Epoch 5/10... Discr. Loss: 0.9132... Generator Loss: 1.8941
Epoch 5/10... Discr. Loss: 1.5930... Generator Loss: 2.0691
Epoch 5/10... Discr. Loss: 1.0124... Generator Loss: 1.3316
Epoch 5/10... Discr. Loss: 0.9217... Generator Loss: 1.6148
Epoch 5/10... Discr. Loss: 0.9237... Generator Loss: 1.5360
Epoch 5/10... Discr. Loss: 0.9028... Generator Loss: 1.3554
Epoch 5/10... Discr. Loss: 0.9407... Generator Loss: 1.3223
Epoch 5/10... Discr. Loss: 0.9150... Generator Loss: 1.1299
Epoch 5/10... Discr. Loss: 1.0396... Generator Loss: 1.1502
Epoch 5/10... Discr. Loss: 0.9687... Generator Loss: 1.0290
Epoch 5/10... Discr. Loss: 0.8547... Generator Loss: 1.8550
Epoch 5/10... Discr. Loss: 1.4360... Generator Loss: 1.5044
Epoch 5/10... Discr. Loss: 0.9179... Generator Loss: 1.2439
Epoch 5/10... Discr. Loss: 0.9046... Generator Loss: 1.3028
Epoch 5/10... Discr. Loss: 1.0258... Generator Loss: 1.1064
Epoch 5/10... Discr. Loss: 1.0770... Generator Loss: 0.9836
Epoch 5/10... Discr. Loss: 1.1033... Generator Loss: 0.8830
Epoch 5/10... Discr. Loss: 1.0743... Generator Loss: 1.7960
Epoch 5/10... Discr. Loss: 1.0164... Generator Loss: 1.0308
Epoch 5/10... Discr. Loss: 0.9074... Generator Loss: 1.3070
Epoch 5/10... Discr. Loss: 0.9642... Generator Loss: 1.5426
Epoch 5/10... Discr. Loss: 1.0482... Generator Loss: 0.8740
Epoch 5/10... Discr. Loss: 1.0357... Generator Loss: 1.0825
Epoch 5/10... Discr. Loss: 0.8967... Generator Loss: 1.2317
Epoch 5/10... Discr. Loss: 0.8892... Generator Loss: 1.4405
Epoch 5/10... Discr. Loss: 0.7831... Generator Loss: 1.4544
Epoch 5/10... Discr. Loss: 0.8722... Generator Loss: 1.1598
Epoch 5/10... Discr. Loss: 0.9815... Generator Loss: 1.8349
Epoch 5/10... Discr. Loss: 0.9224... Generator Loss: 1.7308
Epoch 5/10... Discr. Loss: 1.1643... Generator Loss: 0.7402
Epoch 5/10... Discr. Loss: 0.9145... Generator Loss: 1.6153
Epoch 5/10... Discr. Loss: 0.8570... Generator Loss: 1.4923
Epoch 5/10... Discr. Loss: 0.8317... Generator Loss: 1.3417
Epoch 5/10... Discr. Loss: 0.8314... Generator Loss: 1.8647
Epoch 5/10... Discr. Loss: 0.9204... Generator Loss: 1.5212
Epoch 5/10... Discr. Loss: 0.8698... Generator Loss: 2.1233
Epoch 5/10... Discr. Loss: 1.7231... Generator Loss: 1.5720
Epoch 5/10... Discr. Loss: 0.9104... Generator Loss: 1.9289
Epoch 5/10... Discr. Loss: 0.9414... Generator Loss: 1.8228
Epoch 5/10... Discr. Loss: 1.8199... Generator Loss: 1.1543
Epoch 5/10... Discr. Loss: 0.8180... Generator Loss: 1.3815
Epoch 5/10... Discr. Loss: 0.8295... Generator Loss: 1.5566
Epoch 5/10... Discr. Loss: 0.7933... Generator Loss: 1.6293
Epoch 5/10... Discr. Loss: 0.8621... Generator Loss: 1.3718
Epoch 5/10... Discr. Loss: 1.1668... Generator Loss: 2.1582
Epoch 5/10... Discr. Loss: 1.2492... Generator Loss: 0.6627
Epoch 5/10... Discr. Loss: 0.8621... Generator Loss: 1.6242
Epoch 5/10... Discr. Loss: 0.8452... Generator Loss: 1.2014
Epoch 5/10... Discr. Loss: 0.9695... Generator Loss: 1.5803
Epoch 5/10... Discr. Loss: 0.9083... Generator Loss: 1.6546
Epoch 5/10... Discr. Loss: 0.8033... Generator Loss: 1.6482
Epoch 5/10... Discr. Loss: 1.1841... Generator Loss: 0.7290
Epoch 5/10... Discr. Loss: 0.7501... Generator Loss: 1.6757
Epoch 5/10... Discr. Loss: 0.8470... Generator Loss: 1.2985
Epoch 5/10... Discr. Loss: 0.8136... Generator Loss: 1.3690
Epoch 5/10... Discr. Loss: 1.0131... Generator Loss: 1.2118
Epoch 5/10... Discr. Loss: 0.8582... Generator Loss: 1.7913
Epoch 5/10... Discr. Loss: 1.1968... Generator Loss: 2.5462
Epoch 5/10... Discr. Loss: 1.1184... Generator Loss: 1.2334
Epoch 5/10... Discr. Loss: 0.8627... Generator Loss: 1.7140
Epoch 5/10... Discr. Loss: 0.9282... Generator Loss: 1.6716
Epoch 5/10... Discr. Loss: 1.0277... Generator Loss: 0.9725
Epoch 5/10... Discr. Loss: 0.8481... Generator Loss: 1.8594
Epoch 5/10... Discr. Loss: 0.8254... Generator Loss: 1.8047
Epoch 5/10... Discr. Loss: 0.8908... Generator Loss: 1.8256
Epoch 5/10... Discr. Loss: 0.8205... Generator Loss: 1.4604
Epoch 5/10... Discr. Loss: 0.9226... Generator Loss: 1.3005
Epoch 5/10... Discr. Loss: 1.2508... Generator Loss: 2.6311
Epoch 5/10... Discr. Loss: 1.1508... Generator Loss: 1.2501
Epoch 5/10... Discr. Loss: 0.7846... Generator Loss: 1.5822
Epoch 5/10... Discr. Loss: 1.2137... Generator Loss: 2.5244
Epoch 6/10... Discr. Loss: 0.8086... Generator Loss: 1.6235
Epoch 6/10... Discr. Loss: 0.7986... Generator Loss: 1.9620
Epoch 6/10... Discr. Loss: 0.7711... Generator Loss: 1.6567
Epoch 6/10... Discr. Loss: 0.7668... Generator Loss: 1.6718
Epoch 6/10... Discr. Loss: 0.8095... Generator Loss: 1.3691
Epoch 6/10... Discr. Loss: 0.8323... Generator Loss: 1.7185
Epoch 6/10... Discr. Loss: 0.7289... Generator Loss: 1.8739
Epoch 6/10... Discr. Loss: 1.0174... Generator Loss: 0.9171
Epoch 6/10... Discr. Loss: 1.1367... Generator Loss: 0.7974
Epoch 6/10... Discr. Loss: 1.0114... Generator Loss: 2.1148
Epoch 6/10... Discr. Loss: 0.7840... Generator Loss: 1.5699
Epoch 6/10... Discr. Loss: 0.7214... Generator Loss: 1.6698
Epoch 6/10... Discr. Loss: 1.1546... Generator Loss: 0.7258
Epoch 6/10... Discr. Loss: 0.6868... Generator Loss: 1.5868
Epoch 6/10... Discr. Loss: 0.8513... Generator Loss: 1.4332
Epoch 6/10... Discr. Loss: 0.7003... Generator Loss: 1.6734
Epoch 6/10... Discr. Loss: 0.8757... Generator Loss: 1.2976
Epoch 6/10... Discr. Loss: 1.8740... Generator Loss: 0.8580
Epoch 6/10... Discr. Loss: 1.0538... Generator Loss: 1.6869
Epoch 6/10... Discr. Loss: 0.8363... Generator Loss: 1.6220
Epoch 6/10... Discr. Loss: 0.7833... Generator Loss: 1.6854
Epoch 6/10... Discr. Loss: 1.0131... Generator Loss: 2.5369
Epoch 6/10... Discr. Loss: 0.8202... Generator Loss: 1.3628
Epoch 6/10... Discr. Loss: 0.7588... Generator Loss: 1.3246
Epoch 6/10... Discr. Loss: 0.9744... Generator Loss: 1.9662
Epoch 6/10... Discr. Loss: 0.7880... Generator Loss: 1.3656
Epoch 6/10... Discr. Loss: 0.7517... Generator Loss: 1.6133
Epoch 6/10... Discr. Loss: 0.6828... Generator Loss: 1.6674
Epoch 6/10... Discr. Loss: 0.7611... Generator Loss: 2.1120
Epoch 6/10... Discr. Loss: 0.7314... Generator Loss: 1.4390
Epoch 6/10... Discr. Loss: 1.1330... Generator Loss: 0.8898
Epoch 6/10... Discr. Loss: 1.0548... Generator Loss: 1.4688
Epoch 6/10... Discr. Loss: 0.7860... Generator Loss: 1.9197
Epoch 6/10... Discr. Loss: 0.7672... Generator Loss: 2.2507
Epoch 6/10... Discr. Loss: 0.8037... Generator Loss: 1.5737
Epoch 6/10... Discr. Loss: 0.8086... Generator Loss: 1.4656
Epoch 6/10... Discr. Loss: 0.7447... Generator Loss: 1.4124
Epoch 6/10... Discr. Loss: 1.1148... Generator Loss: 0.8765
Epoch 6/10... Discr. Loss: 0.7543... Generator Loss: 1.7163
Epoch 6/10... Discr. Loss: 0.6717... Generator Loss: 2.3219
Epoch 6/10... Discr. Loss: 0.7991... Generator Loss: 1.4465
Epoch 6/10... Discr. Loss: 0.7567... Generator Loss: 2.1377
Epoch 6/10... Discr. Loss: 0.6962... Generator Loss: 1.9550
Epoch 6/10... Discr. Loss: 0.8293... Generator Loss: 1.2485
Epoch 6/10... Discr. Loss: 0.6878... Generator Loss: 1.7081
Epoch 6/10... Discr. Loss: 1.7065... Generator Loss: 0.4362
Epoch 6/10... Discr. Loss: 0.8205... Generator Loss: 2.1161
Epoch 6/10... Discr. Loss: 0.6745... Generator Loss: 1.8754
Epoch 6/10... Discr. Loss: 0.6701... Generator Loss: 1.9824
Epoch 6/10... Discr. Loss: 0.7622... Generator Loss: 1.5022
Epoch 6/10... Discr. Loss: 0.6434... Generator Loss: 1.8702
Epoch 6/10... Discr. Loss: 0.8307... Generator Loss: 2.5464
Epoch 6/10... Discr. Loss: 0.7114... Generator Loss: 1.6207
Epoch 6/10... Discr. Loss: 0.9160... Generator Loss: 1.1950
Epoch 6/10... Discr. Loss: 0.6509... Generator Loss: 1.7403
Epoch 6/10... Discr. Loss: 0.7172... Generator Loss: 1.4584
Epoch 6/10... Discr. Loss: 0.7799... Generator Loss: 2.5988
Epoch 6/10... Discr. Loss: 1.1249... Generator Loss: 1.6217
Epoch 6/10... Discr. Loss: 0.7636... Generator Loss: 1.4637
Epoch 6/10... Discr. Loss: 0.6761... Generator Loss: 2.3456
Epoch 6/10... Discr. Loss: 0.8709... Generator Loss: 2.7247
Epoch 6/10... Discr. Loss: 1.0798... Generator Loss: 3.0155
Epoch 6/10... Discr. Loss: 0.6720... Generator Loss: 1.8106
Epoch 6/10... Discr. Loss: 0.8917... Generator Loss: 2.6078
Epoch 6/10... Discr. Loss: 1.0916... Generator Loss: 3.0577
Epoch 6/10... Discr. Loss: 0.9219... Generator Loss: 1.1187
Epoch 6/10... Discr. Loss: 0.6987... Generator Loss: 1.6379
Epoch 6/10... Discr. Loss: 0.6706... Generator Loss: 1.7041
Epoch 6/10... Discr. Loss: 0.7436... Generator Loss: 2.7893
Epoch 6/10... Discr. Loss: 0.7911... Generator Loss: 1.4946
Epoch 6/10... Discr. Loss: 0.6945... Generator Loss: 2.4175
Epoch 6/10... Discr. Loss: 0.7474... Generator Loss: 2.4300
Epoch 6/10... Discr. Loss: 1.7092... Generator Loss: 1.5056
Epoch 6/10... Discr. Loss: 0.6684... Generator Loss: 2.3086
Epoch 6/10... Discr. Loss: 0.8357... Generator Loss: 1.2990
Epoch 6/10... Discr. Loss: 0.7083... Generator Loss: 2.5448
Epoch 6/10... Discr. Loss: 0.5623... Generator Loss: 2.1822
Epoch 6/10... Discr. Loss: 0.6419... Generator Loss: 1.8392
Epoch 6/10... Discr. Loss: 0.6963... Generator Loss: 2.5012
Epoch 6/10... Discr. Loss: 0.6827... Generator Loss: 1.7369
Epoch 6/10... Discr. Loss: 0.6716... Generator Loss: 2.4567
Epoch 6/10... Discr. Loss: 1.0484... Generator Loss: 3.1202
Epoch 6/10... Discr. Loss: 0.9973... Generator Loss: 1.0723
Epoch 6/10... Discr. Loss: 0.6530... Generator Loss: 2.0559
Epoch 6/10... Discr. Loss: 0.6220... Generator Loss: 2.4316
Epoch 6/10... Discr. Loss: 0.6334... Generator Loss: 2.4208
Epoch 6/10... Discr. Loss: 0.6786... Generator Loss: 2.3098
Epoch 6/10... Discr. Loss: 0.6313... Generator Loss: 2.1541
Epoch 6/10... Discr. Loss: 0.9202... Generator Loss: 2.5939
Epoch 6/10... Discr. Loss: 0.6963... Generator Loss: 1.6065
Epoch 6/10... Discr. Loss: 0.5818... Generator Loss: 2.0692
Epoch 6/10... Discr. Loss: 0.7183... Generator Loss: 1.5611
Epoch 6/10... Discr. Loss: 0.8651... Generator Loss: 2.9666
Epoch 6/10... Discr. Loss: 0.6478... Generator Loss: 1.6724
Epoch 6/10... Discr. Loss: 0.8146... Generator Loss: 1.4267
Epoch 6/10... Discr. Loss: 0.6292... Generator Loss: 2.3660
Epoch 6/10... Discr. Loss: 0.6260... Generator Loss: 2.5024
Epoch 6/10... Discr. Loss: 0.6315... Generator Loss: 2.4437
Epoch 6/10... Discr. Loss: 0.5403... Generator Loss: 2.3182
Epoch 6/10... Discr. Loss: 2.5690... Generator Loss: 2.2152
Epoch 6/10... Discr. Loss: 0.8670... Generator Loss: 2.1988
Epoch 6/10... Discr. Loss: 0.7435... Generator Loss: 1.5392
Epoch 6/10... Discr. Loss: 0.6660... Generator Loss: 2.1827
Epoch 6/10... Discr. Loss: 0.5959... Generator Loss: 2.3530
Epoch 6/10... Discr. Loss: 0.5430... Generator Loss: 2.1836
Epoch 6/10... Discr. Loss: 0.9262... Generator Loss: 1.0675
Epoch 6/10... Discr. Loss: 0.9812... Generator Loss: 1.1853
Epoch 6/10... Discr. Loss: 0.5828... Generator Loss: 2.4606
Epoch 6/10... Discr. Loss: 0.5347... Generator Loss: 2.2957
Epoch 6/10... Discr. Loss: 0.6470... Generator Loss: 1.9655
Epoch 6/10... Discr. Loss: 0.9163... Generator Loss: 2.8164
Epoch 6/10... Discr. Loss: 0.8993... Generator Loss: 2.6820
Epoch 6/10... Discr. Loss: 0.7464... Generator Loss: 1.3473
Epoch 6/10... Discr. Loss: 0.6218... Generator Loss: 2.1429
Epoch 6/10... Discr. Loss: 0.5305... Generator Loss: 2.1851
Epoch 6/10... Discr. Loss: 0.6181... Generator Loss: 2.6302
Epoch 6/10... Discr. Loss: 0.5655... Generator Loss: 2.0964
Epoch 6/10... Discr. Loss: 0.5297... Generator Loss: 2.5824
Epoch 6/10... Discr. Loss: 0.7779... Generator Loss: 2.9909
Epoch 6/10... Discr. Loss: 1.0061... Generator Loss: 2.2579
Epoch 6/10... Discr. Loss: 0.5765... Generator Loss: 2.1431
Epoch 6/10... Discr. Loss: 0.5608... Generator Loss: 2.3501
Epoch 6/10... Discr. Loss: 0.6774... Generator Loss: 2.7449
Epoch 6/10... Discr. Loss: 0.7029... Generator Loss: 1.5934
Epoch 6/10... Discr. Loss: 0.6014... Generator Loss: 2.4378
Epoch 6/10... Discr. Loss: 0.6843... Generator Loss: 1.5399
Epoch 6/10... Discr. Loss: 0.5982... Generator Loss: 2.2856
Epoch 6/10... Discr. Loss: 0.5938... Generator Loss: 2.2452
Epoch 6/10... Discr. Loss: 1.3335... Generator Loss: 0.7333
Epoch 6/10... Discr. Loss: 0.8751... Generator Loss: 2.1736
Epoch 6/10... Discr. Loss: 0.5750... Generator Loss: 2.1945
Epoch 6/10... Discr. Loss: 0.6865... Generator Loss: 1.9344
Epoch 6/10... Discr. Loss: 0.6007... Generator Loss: 2.5599
Epoch 6/10... Discr. Loss: 0.7699... Generator Loss: 3.0802
Epoch 6/10... Discr. Loss: 0.5464... Generator Loss: 2.3059
Epoch 6/10... Discr. Loss: 1.6448... Generator Loss: 2.2793
Epoch 6/10... Discr. Loss: 1.2541... Generator Loss: 1.3430
Epoch 6/10... Discr. Loss: 0.6803... Generator Loss: 1.9319
Epoch 6/10... Discr. Loss: 0.6940... Generator Loss: 1.7273
Epoch 6/10... Discr. Loss: 0.5951... Generator Loss: 2.3317
Epoch 6/10... Discr. Loss: 0.6060... Generator Loss: 2.5304
Epoch 6/10... Discr. Loss: 0.5872... Generator Loss: 2.3067
Epoch 6/10... Discr. Loss: 0.5545... Generator Loss: 2.4823
Epoch 6/10... Discr. Loss: 0.5520... Generator Loss: 1.9205
Epoch 6/10... Discr. Loss: 0.7450... Generator Loss: 3.0206
Epoch 6/10... Discr. Loss: 0.8063... Generator Loss: 1.2510
Epoch 6/10... Discr. Loss: 0.5991... Generator Loss: 2.4458
Epoch 6/10... Discr. Loss: 0.5418... Generator Loss: 2.4895
Epoch 6/10... Discr. Loss: 0.5797... Generator Loss: 2.0746
Epoch 6/10... Discr. Loss: 0.5910... Generator Loss: 2.2505
Epoch 6/10... Discr. Loss: 0.6098... Generator Loss: 1.5780
Epoch 6/10... Discr. Loss: 0.7370... Generator Loss: 3.5886
Epoch 6/10... Discr. Loss: 0.6099... Generator Loss: 1.8840
Epoch 6/10... Discr. Loss: 0.5409... Generator Loss: 2.6388
Epoch 6/10... Discr. Loss: 0.5751... Generator Loss: 1.9447
Epoch 6/10... Discr. Loss: 0.5738... Generator Loss: 3.3038
Epoch 6/10... Discr. Loss: 0.5965... Generator Loss: 2.0397
Epoch 6/10... Discr. Loss: 0.6448... Generator Loss: 1.7244
Epoch 7/10... Discr. Loss: 0.7530... Generator Loss: 2.7447
Epoch 7/10... Discr. Loss: 0.5644... Generator Loss: 3.2143
Epoch 7/10... Discr. Loss: 0.5728... Generator Loss: 2.7520
Epoch 7/10... Discr. Loss: 0.6223... Generator Loss: 1.7290
Epoch 7/10... Discr. Loss: 0.5275... Generator Loss: 2.6156
Epoch 7/10... Discr. Loss: 0.5452... Generator Loss: 3.0369
Epoch 7/10... Discr. Loss: 0.5565... Generator Loss: 2.6812
Epoch 7/10... Discr. Loss: 1.5500... Generator Loss: 0.6919
Epoch 7/10... Discr. Loss: 2.1366... Generator Loss: 1.1827
Epoch 7/10... Discr. Loss: 1.0031... Generator Loss: 1.6896
Epoch 7/10... Discr. Loss: 0.6743... Generator Loss: 1.7241
Epoch 7/10... Discr. Loss: 0.6507... Generator Loss: 2.1254
Epoch 7/10... Discr. Loss: 0.5303... Generator Loss: 2.2724
Epoch 7/10... Discr. Loss: 0.5497... Generator Loss: 2.4796
Epoch 7/10... Discr. Loss: 0.5727... Generator Loss: 2.4900
Epoch 7/10... Discr. Loss: 0.5181... Generator Loss: 2.3567
Epoch 7/10... Discr. Loss: 0.5994... Generator Loss: 1.8241
Epoch 7/10... Discr. Loss: 0.6645... Generator Loss: 1.8976
Epoch 7/10... Discr. Loss: 0.5668... Generator Loss: 1.9259
Epoch 7/10... Discr. Loss: 0.4793... Generator Loss: 2.6056
Epoch 7/10... Discr. Loss: 0.5418... Generator Loss: 2.0600
Epoch 7/10... Discr. Loss: 1.3101... Generator Loss: 3.6299
Epoch 7/10... Discr. Loss: 0.8646... Generator Loss: 1.9339
Epoch 7/10... Discr. Loss: 0.5758... Generator Loss: 2.5759
Epoch 7/10... Discr. Loss: 0.5932... Generator Loss: 2.2262
Epoch 7/10... Discr. Loss: 0.5691... Generator Loss: 1.9880
Epoch 7/10... Discr. Loss: 0.5665... Generator Loss: 3.2737
Epoch 7/10... Discr. Loss: 0.9202... Generator Loss: 1.1682
Epoch 7/10... Discr. Loss: 0.6320... Generator Loss: 3.1124
Epoch 7/10... Discr. Loss: 0.5648... Generator Loss: 2.1420
Epoch 7/10... Discr. Loss: 0.6612... Generator Loss: 1.9720
Epoch 7/10... Discr. Loss: 0.5376... Generator Loss: 2.8255
Epoch 7/10... Discr. Loss: 0.5545... Generator Loss: 2.0689
Epoch 7/10... Discr. Loss: 0.9579... Generator Loss: 1.1631
Epoch 7/10... Discr. Loss: 0.6141... Generator Loss: 2.6647
Epoch 7/10... Discr. Loss: 0.5545... Generator Loss: 1.7614
Epoch 7/10... Discr. Loss: 0.6251... Generator Loss: 1.8525
Epoch 7/10... Discr. Loss: 0.4757... Generator Loss: 3.1042
Epoch 7/10... Discr. Loss: 0.6285... Generator Loss: 3.0043
Epoch 7/10... Discr. Loss: 0.5999... Generator Loss: 2.3318
Epoch 7/10... Discr. Loss: 0.6394... Generator Loss: 1.5779
Epoch 7/10... Discr. Loss: 0.4537... Generator Loss: 2.7885
Epoch 7/10... Discr. Loss: 0.5466... Generator Loss: 2.3099
Epoch 7/10... Discr. Loss: 0.5593... Generator Loss: 3.1077
Epoch 7/10... Discr. Loss: 0.5461... Generator Loss: 2.0588
Epoch 7/10... Discr. Loss: 0.6391... Generator Loss: 1.6689
Epoch 7/10... Discr. Loss: 2.4261... Generator Loss: 0.6182
Epoch 7/10... Discr. Loss: 0.6362... Generator Loss: 1.9394
Epoch 7/10... Discr. Loss: 0.5391... Generator Loss: 2.4695
Epoch 7/10... Discr. Loss: 0.6130... Generator Loss: 2.4617
Epoch 7/10... Discr. Loss: 0.6557... Generator Loss: 1.8713
Epoch 7/10... Discr. Loss: 0.5660... Generator Loss: 2.0189
Epoch 7/10... Discr. Loss: 0.5754... Generator Loss: 2.0144
Epoch 7/10... Discr. Loss: 1.3977... Generator Loss: 0.6625
Epoch 7/10... Discr. Loss: 0.6476... Generator Loss: 2.2101
Epoch 7/10... Discr. Loss: 0.6689... Generator Loss: 1.8105
Epoch 7/10... Discr. Loss: 0.4631... Generator Loss: 2.4732
Epoch 7/10... Discr. Loss: 0.5620... Generator Loss: 2.0884
Epoch 7/10... Discr. Loss: 0.5821... Generator Loss: 1.9911
Epoch 7/10... Discr. Loss: 0.5090... Generator Loss: 2.7043
Epoch 7/10... Discr. Loss: 0.4661... Generator Loss: 2.3712
Epoch 7/10... Discr. Loss: 0.5115... Generator Loss: 2.1663
Epoch 7/10... Discr. Loss: 0.4648... Generator Loss: 2.5422
Epoch 7/10... Discr. Loss: 0.8968... Generator Loss: 3.2022
Epoch 7/10... Discr. Loss: 0.7802... Generator Loss: 1.9623
Epoch 7/10... Discr. Loss: 0.5397... Generator Loss: 2.5759
Epoch 7/10... Discr. Loss: 0.4893... Generator Loss: 2.3397
Epoch 7/10... Discr. Loss: 0.6541... Generator Loss: 2.6817
Epoch 7/10... Discr. Loss: 0.4686... Generator Loss: 2.6307
Epoch 7/10... Discr. Loss: 0.5081... Generator Loss: 2.3798
Epoch 7/10... Discr. Loss: 0.8000... Generator Loss: 3.6453
Epoch 7/10... Discr. Loss: 0.4654... Generator Loss: 2.6705
Epoch 7/10... Discr. Loss: 0.6020... Generator Loss: 1.8283
Epoch 7/10... Discr. Loss: 0.4826... Generator Loss: 3.0737
Epoch 7/10... Discr. Loss: 0.6054... Generator Loss: 3.2085
Epoch 7/10... Discr. Loss: 0.4913... Generator Loss: 3.1219
Epoch 7/10... Discr. Loss: 0.5649... Generator Loss: 1.9868
Epoch 7/10... Discr. Loss: 0.6157... Generator Loss: 1.8686
Epoch 7/10... Discr. Loss: 0.8366... Generator Loss: 1.5516
Epoch 7/10... Discr. Loss: 0.5095... Generator Loss: 2.5858
Epoch 7/10... Discr. Loss: 0.4678... Generator Loss: 2.6819
Epoch 7/10... Discr. Loss: 0.8222... Generator Loss: 3.7220
Epoch 7/10... Discr. Loss: 0.5863... Generator Loss: 1.9583
Epoch 7/10... Discr. Loss: 0.7839... Generator Loss: 2.8750
Epoch 7/10... Discr. Loss: 0.4814... Generator Loss: 2.5259
Epoch 7/10... Discr. Loss: 0.4842... Generator Loss: 2.6542
Epoch 7/10... Discr. Loss: 0.4649... Generator Loss: 2.9802
Epoch 7/10... Discr. Loss: 0.4848... Generator Loss: 2.5337
Epoch 7/10... Discr. Loss: 0.5405... Generator Loss: 2.7563
Epoch 7/10... Discr. Loss: 0.7629... Generator Loss: 3.5828
Epoch 7/10... Discr. Loss: 0.4551... Generator Loss: 2.9191
Epoch 7/10... Discr. Loss: 0.6119... Generator Loss: 1.7912
Epoch 7/10... Discr. Loss: 0.5106... Generator Loss: 2.8739
Epoch 7/10... Discr. Loss: 0.6393... Generator Loss: 1.8201
Epoch 7/10... Discr. Loss: 0.4790... Generator Loss: 2.8631
Epoch 7/10... Discr. Loss: 0.4396... Generator Loss: 2.8696
Epoch 7/10... Discr. Loss: 0.4794... Generator Loss: 2.3158
Epoch 7/10... Discr. Loss: 0.6343... Generator Loss: 2.3365
Epoch 7/10... Discr. Loss: 3.1617... Generator Loss: 5.0743
Epoch 7/10... Discr. Loss: 0.7746... Generator Loss: 2.2204
Epoch 7/10... Discr. Loss: 0.5495... Generator Loss: 2.2048
Epoch 7/10... Discr. Loss: 0.6244... Generator Loss: 2.1035
Epoch 7/10... Discr. Loss: 0.6230... Generator Loss: 2.2457
Epoch 7/10... Discr. Loss: 0.6059... Generator Loss: 1.9843
Epoch 7/10... Discr. Loss: 0.4855... Generator Loss: 2.4676
Epoch 7/10... Discr. Loss: 0.5489... Generator Loss: 2.2033
Epoch 7/10... Discr. Loss: 0.4487... Generator Loss: 3.1707
Epoch 7/10... Discr. Loss: 0.4571... Generator Loss: 2.6011
Epoch 7/10... Discr. Loss: 0.4310... Generator Loss: 3.0167
Epoch 7/10... Discr. Loss: 0.5424... Generator Loss: 2.1359
Epoch 7/10... Discr. Loss: 0.4788... Generator Loss: 2.6198
Epoch 7/10... Discr. Loss: 0.4093... Generator Loss: 3.8749
Epoch 7/10... Discr. Loss: 0.4603... Generator Loss: 2.9631
Epoch 7/10... Discr. Loss: 0.4551... Generator Loss: 2.7368
Epoch 7/10... Discr. Loss: 1.0363... Generator Loss: 1.9376
Epoch 7/10... Discr. Loss: 1.8345... Generator Loss: 1.3425
Epoch 7/10... Discr. Loss: 1.9953... Generator Loss: 0.4833
Epoch 7/10... Discr. Loss: 0.5540... Generator Loss: 2.4533
Epoch 7/10... Discr. Loss: 0.6007... Generator Loss: 1.9939
Epoch 7/10... Discr. Loss: 0.4805... Generator Loss: 2.5737
Epoch 7/10... Discr. Loss: 0.6204... Generator Loss: 1.8659
Epoch 7/10... Discr. Loss: 0.5043... Generator Loss: 2.3258
Epoch 7/10... Discr. Loss: 0.4681... Generator Loss: 2.5755
Epoch 7/10... Discr. Loss: 0.6614... Generator Loss: 1.7289
Epoch 7/10... Discr. Loss: 0.5369... Generator Loss: 1.9796
Epoch 7/10... Discr. Loss: 0.7768... Generator Loss: 2.3132
Epoch 7/10... Discr. Loss: 0.4768... Generator Loss: 2.3032
Epoch 7/10... Discr. Loss: 0.4465... Generator Loss: 2.7314
Epoch 7/10... Discr. Loss: 0.4972... Generator Loss: 2.8990
Epoch 7/10... Discr. Loss: 0.4583... Generator Loss: 2.8263
Epoch 7/10... Discr. Loss: 0.4610... Generator Loss: 2.6559
Epoch 7/10... Discr. Loss: 0.4294... Generator Loss: 3.1720
Epoch 7/10... Discr. Loss: 0.4769... Generator Loss: 2.1734
Epoch 7/10... Discr. Loss: 0.4681... Generator Loss: 3.3437
Epoch 7/10... Discr. Loss: 1.0221... Generator Loss: 0.9662
Epoch 7/10... Discr. Loss: 0.6239... Generator Loss: 2.9602
Epoch 7/10... Discr. Loss: 0.4843... Generator Loss: 3.1472
Epoch 7/10... Discr. Loss: 0.4583... Generator Loss: 2.4377
Epoch 7/10... Discr. Loss: 0.8270... Generator Loss: 3.8120
Epoch 7/10... Discr. Loss: 0.5830... Generator Loss: 2.3522
Epoch 7/10... Discr. Loss: 0.4852... Generator Loss: 2.7969
Epoch 7/10... Discr. Loss: 0.5015... Generator Loss: 2.2455
Epoch 7/10... Discr. Loss: 0.4361... Generator Loss: 3.0648
Epoch 7/10... Discr. Loss: 0.4018... Generator Loss: 2.6878
Epoch 7/10... Discr. Loss: 0.4634... Generator Loss: 3.1512
Epoch 7/10... Discr. Loss: 0.4235... Generator Loss: 3.0876
Epoch 7/10... Discr. Loss: 0.4841... Generator Loss: 3.3301
Epoch 7/10... Discr. Loss: 0.4125... Generator Loss: 2.9036
Epoch 7/10... Discr. Loss: 0.3564... Generator Loss: 4.0082
Epoch 7/10... Discr. Loss: 0.4324... Generator Loss: 3.4187
Epoch 7/10... Discr. Loss: 0.4317... Generator Loss: 3.5589
Epoch 7/10... Discr. Loss: 0.6878... Generator Loss: 4.1905
Epoch 7/10... Discr. Loss: 0.8281... Generator Loss: 2.4892
Epoch 7/10... Discr. Loss: 0.5122... Generator Loss: 2.8508
Epoch 7/10... Discr. Loss: 0.6108... Generator Loss: 3.3138
Epoch 7/10... Discr. Loss: 0.4905... Generator Loss: 2.6143
Epoch 7/10... Discr. Loss: 0.4243... Generator Loss: 2.8566
Epoch 7/10... Discr. Loss: 0.3507... Generator Loss: 3.2216
Epoch 8/10... Discr. Loss: 0.8128... Generator Loss: 1.3864
Epoch 8/10... Discr. Loss: 1.1965... Generator Loss: 4.1364
Epoch 8/10... Discr. Loss: 0.5373... Generator Loss: 2.3507
Epoch 8/10... Discr. Loss: 0.5078... Generator Loss: 2.6036
Epoch 8/10... Discr. Loss: 0.6048... Generator Loss: 2.0262
Epoch 8/10... Discr. Loss: 0.4724... Generator Loss: 3.3602
Epoch 8/10... Discr. Loss: 0.4438... Generator Loss: 2.6294
Epoch 8/10... Discr. Loss: 0.4876... Generator Loss: 2.4904
Epoch 8/10... Discr. Loss: 0.8088... Generator Loss: 3.9763
Epoch 8/10... Discr. Loss: 1.1706... Generator Loss: 2.3641
Epoch 8/10... Discr. Loss: 0.6624... Generator Loss: 2.8230
Epoch 8/10... Discr. Loss: 0.5030... Generator Loss: 2.5170
Epoch 8/10... Discr. Loss: 0.4570... Generator Loss: 2.4110
Epoch 8/10... Discr. Loss: 0.4419... Generator Loss: 3.2190
Epoch 8/10... Discr. Loss: 0.4716... Generator Loss: 2.7767
Epoch 8/10... Discr. Loss: 0.4836... Generator Loss: 2.5172
Epoch 8/10... Discr. Loss: 0.4672... Generator Loss: 2.7069
Epoch 8/10... Discr. Loss: 0.9693... Generator Loss: 1.2663
Epoch 8/10... Discr. Loss: 0.4563... Generator Loss: 2.4671
Epoch 8/10... Discr. Loss: 0.4401... Generator Loss: 2.7984
Epoch 8/10... Discr. Loss: 0.4571... Generator Loss: 2.5202
Epoch 8/10... Discr. Loss: 0.4288... Generator Loss: 3.3541
Epoch 8/10... Discr. Loss: 0.5760... Generator Loss: 2.0225
Epoch 8/10... Discr. Loss: 0.5843... Generator Loss: 1.9596
Epoch 8/10... Discr. Loss: 0.4233... Generator Loss: 2.8621
Epoch 8/10... Discr. Loss: 0.4619... Generator Loss: 2.7234
Epoch 8/10... Discr. Loss: 0.3902... Generator Loss: 3.0458
Epoch 8/10... Discr. Loss: 0.4174... Generator Loss: 2.9330
Epoch 8/10... Discr. Loss: 0.4219... Generator Loss: 3.6346
Epoch 8/10... Discr. Loss: 0.4192... Generator Loss: 3.8812
Epoch 8/10... Discr. Loss: 0.6022... Generator Loss: 1.8705
Epoch 8/10... Discr. Loss: 0.4264... Generator Loss: 3.4623
Epoch 8/10... Discr. Loss: 0.4857... Generator Loss: 2.3889
Epoch 8/10... Discr. Loss: 0.4256... Generator Loss: 3.0417
Epoch 8/10... Discr. Loss: 0.4673... Generator Loss: 2.5096
Epoch 8/10... Discr. Loss: 0.5245... Generator Loss: 2.2699
Epoch 8/10... Discr. Loss: 1.0707... Generator Loss: 4.1511
Epoch 8/10... Discr. Loss: 0.9339... Generator Loss: 3.6330
Epoch 8/10... Discr. Loss: 0.4551... Generator Loss: 3.1509
Epoch 8/10... Discr. Loss: 0.4074... Generator Loss: 3.0541
Epoch 8/10... Discr. Loss: 0.4333... Generator Loss: 2.9973
Epoch 8/10... Discr. Loss: 0.4552... Generator Loss: 2.4721
Epoch 8/10... Discr. Loss: 0.4850... Generator Loss: 2.9508
Epoch 8/10... Discr. Loss: 0.4527... Generator Loss: 2.7359
Epoch 8/10... Discr. Loss: 0.4334... Generator Loss: 3.3065
Epoch 8/10... Discr. Loss: 0.7545... Generator Loss: 1.5595
Epoch 8/10... Discr. Loss: 1.1622... Generator Loss: 1.4532
Epoch 8/10... Discr. Loss: 0.6603... Generator Loss: 3.5630
Epoch 8/10... Discr. Loss: 0.4302... Generator Loss: 2.6558
Epoch 8/10... Discr. Loss: 0.4257... Generator Loss: 3.3002
Epoch 8/10... Discr. Loss: 0.5512... Generator Loss: 3.8131
Epoch 8/10... Discr. Loss: 0.4784... Generator Loss: 3.4802
Epoch 8/10... Discr. Loss: 0.4374... Generator Loss: 2.4387
Epoch 8/10... Discr. Loss: 0.4866... Generator Loss: 2.3751
Epoch 8/10... Discr. Loss: 0.3903... Generator Loss: 2.9803
Epoch 8/10... Discr. Loss: 0.6021... Generator Loss: 1.8032
Epoch 8/10... Discr. Loss: 0.3793... Generator Loss: 3.1466
Epoch 8/10... Discr. Loss: 0.4384... Generator Loss: 2.7461
Epoch 8/10... Discr. Loss: 0.3835... Generator Loss: 3.0163
Epoch 8/10... Discr. Loss: 0.5210... Generator Loss: 4.0802
Epoch 8/10... Discr. Loss: 4.2252... Generator Loss: 4.2249
Epoch 8/10... Discr. Loss: 1.1100... Generator Loss: 1.8669
Epoch 8/10... Discr. Loss: 0.8109... Generator Loss: 3.1386
Epoch 8/10... Discr. Loss: 1.3114... Generator Loss: 0.9965
Epoch 8/10... Discr. Loss: 0.6381... Generator Loss: 2.2482
Epoch 8/10... Discr. Loss: 0.9307... Generator Loss: 1.2562
Epoch 8/10... Discr. Loss: 0.5029... Generator Loss: 2.8026
Epoch 8/10... Discr. Loss: 0.4842... Generator Loss: 2.5372
Epoch 8/10... Discr. Loss: 0.5101... Generator Loss: 2.2922
Epoch 8/10... Discr. Loss: 0.4502... Generator Loss: 2.9192
Epoch 8/10... Discr. Loss: 0.5347... Generator Loss: 3.5945
Epoch 8/10... Discr. Loss: 0.4419... Generator Loss: 3.0189
Epoch 8/10... Discr. Loss: 0.4511... Generator Loss: 2.9679
Epoch 8/10... Discr. Loss: 0.4170... Generator Loss: 3.2399
Epoch 8/10... Discr. Loss: 0.3817... Generator Loss: 3.1829
Epoch 8/10... Discr. Loss: 0.8493... Generator Loss: 1.2769
Epoch 8/10... Discr. Loss: 0.4524... Generator Loss: 2.8720
Epoch 8/10... Discr. Loss: 0.4260... Generator Loss: 2.9213
Epoch 8/10... Discr. Loss: 0.5167... Generator Loss: 3.5042
Epoch 8/10... Discr. Loss: 0.4508... Generator Loss: 2.7107
Epoch 8/10... Discr. Loss: 0.3927... Generator Loss: 3.1717
Epoch 8/10... Discr. Loss: 0.4446... Generator Loss: 3.3751
Epoch 8/10... Discr. Loss: 0.4095... Generator Loss: 2.9374
Epoch 8/10... Discr. Loss: 0.3965... Generator Loss: 2.6751
Epoch 8/10... Discr. Loss: 0.6460... Generator Loss: 3.8286
Epoch 8/10... Discr. Loss: 0.4867... Generator Loss: 2.2614
Epoch 8/10... Discr. Loss: 0.4454... Generator Loss: 3.4879
Epoch 8/10... Discr. Loss: 0.4053... Generator Loss: 3.0130
Epoch 8/10... Discr. Loss: 0.3973... Generator Loss: 3.5407
Epoch 8/10... Discr. Loss: 0.3817... Generator Loss: 3.3631
Epoch 8/10... Discr. Loss: 0.3924... Generator Loss: 3.2679
Epoch 8/10... Discr. Loss: 0.4712... Generator Loss: 3.3385
Epoch 8/10... Discr. Loss: 0.6650... Generator Loss: 2.6511
Epoch 8/10... Discr. Loss: 0.3863... Generator Loss: 3.5069
Epoch 8/10... Discr. Loss: 0.4998... Generator Loss: 2.5259
Epoch 8/10... Discr. Loss: 0.3474... Generator Loss: 3.6799
Epoch 8/10... Discr. Loss: 0.3870... Generator Loss: 2.9815
Epoch 8/10... Discr. Loss: 0.5281... Generator Loss: 2.3440
Epoch 8/10... Discr. Loss: 0.3944... Generator Loss: 3.1937
Epoch 8/10... Discr. Loss: 0.6035... Generator Loss: 4.1999
Epoch 8/10... Discr. Loss: 1.0118... Generator Loss: 1.1342
Epoch 8/10... Discr. Loss: 0.7923... Generator Loss: 3.6967
Epoch 8/10... Discr. Loss: 0.5403... Generator Loss: 1.7872
Epoch 8/10... Discr. Loss: 0.4703... Generator Loss: 2.3149
Epoch 8/10... Discr. Loss: 0.3999... Generator Loss: 2.8223
Epoch 8/10... Discr. Loss: 0.4598... Generator Loss: 2.8506
Epoch 8/10... Discr. Loss: 0.4001... Generator Loss: 3.5103
Epoch 8/10... Discr. Loss: 0.4387... Generator Loss: 2.6886
Epoch 8/10... Discr. Loss: 0.3552... Generator Loss: 2.8870
Epoch 8/10... Discr. Loss: 0.3943... Generator Loss: 3.3044
Epoch 8/10... Discr. Loss: 0.4812... Generator Loss: 3.7410
Epoch 8/10... Discr. Loss: 0.5982... Generator Loss: 4.0183
Epoch 8/10... Discr. Loss: 0.6081... Generator Loss: 3.6651
Epoch 8/10... Discr. Loss: 0.4571... Generator Loss: 3.5043
Epoch 8/10... Discr. Loss: 0.3403... Generator Loss: 3.7320
Epoch 8/10... Discr. Loss: 0.5588... Generator Loss: 2.5566
Epoch 8/10... Discr. Loss: 0.4596... Generator Loss: 3.6418
Epoch 8/10... Discr. Loss: 0.3787... Generator Loss: 3.3352
---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
<ipython-input-20-bc5d59207896> in <module>
     13 with tf.Graph().as_default():
     14     train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
---> 15           celeba_dataset.shape, celeba_dataset.image_mode)

<ipython-input-19-4a80ada67dee> in train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode)
     37                 # Run optimizers
     38                 _ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, l_r: learning_rate})
---> 39                 _ = sess.run(g_opt, feed_dict={input_real: batch_images, input_z: batch_z, l_r: learning_rate})
     40 
     41                 if steps % 10 == 0:

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
    875     try:
    876       result = self._run(None, fetches, feed_dict, options_ptr,
--> 877                          run_metadata_ptr)
    878       if run_metadata:
    879         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1098     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1099       results = self._do_run(handle, final_targets, final_fetches,
-> 1100                              feed_dict_tensor, options, run_metadata)
   1101     else:
   1102       results = []

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1270     if handle is None:
   1271       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1272                            run_metadata)
   1273     else:
   1274       return self._do_call(_prun_fn, handle, feeds, fetches)

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
   1276   def _do_call(self, fn, *args):
   1277     try:
-> 1278       return fn(*args)
   1279     except errors.OpError as e:
   1280       message = compat.as_text(e.message)

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1261       self._extend_graph()
   1262       return self._call_tf_sessionrun(
-> 1263           options, feed_dict, fetch_list, target_list, run_metadata)
   1264 
   1265     def _prun_fn(handle, feed_dict, fetch_list):

~\.conda\envs\tf-gpu2\lib\site-packages\tensorflow\python\client\session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1348     return tf_session.TF_SessionRun_wrapper(
   1349         self._session, options, feed_dict, fetch_list, target_list,
-> 1350         run_metadata)
   1351 
   1352   def _call_tf_sessionprun(self, handle, feed_dict, fetch_list):

KeyboardInterrupt: 

Submitting This Project

When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.